AGENT-tier model decision: Sonnet 4.6 vs Sonnet 5

Overnight fleet evaluation, 2026-08-01 → 2026-08-02 · 48 suites · 995 scenarios · both arms on the subscription bearer, graders pinned at claude-sonnet-4-6 · repo ~/.claude/propflowai @ 941860dab (arms) / 3b7f0172c (verification re-runs)

1. Goal and strategy

The goal is not "find the best model." It is to get the AGENT tier off Opus on metered spend without regressing tenant-facing behavior. Today AGENT_MODEL = process.env.CLAUDE_MODEL || 'claude-opus-5' drives the Clara conversation loop, the opt-out compliance classifier, maintenance intake, the turnover attribution judge, Ask Clara, message rationale, topic classification and 11 other production call sites. That is the single largest metered surface we own.

Both candidate Sonnets solve the cost problem identically at list price. So the strategy was to treat this as a regression question, not a benchmark race: run every model-sensitive eval surface in the repo on both Sonnets, and only prefer Sonnet 5 if it is at least at parity everywhere that matters — compliance, escalation contracts, tool correctness, and the turnover/renewal money paths. A tie goes to the incumbent, because the incumbent is the one we have production evidence for.

Every apparent difference was then attacked adversarially: each flipped scenario was re-run 3× per arm, and a flip only counts if the majority outcome differs. Where a win looked like it came from formatting, judge taste, an empty completion, or a token budget rather than behavior, it was probed directly and thrown out.

2. Bottom line

Recommendation: move the AGENT tier to Sonnet 4.6, not Sonnet 5.

Sonnet 4.6 captures the entire cost objective (Opus-tier → Sonnet-tier) with the fewest open behavioral questions. Across 48 suites, 35 are parity, 10 favor Sonnet 4.6, and 3 favor Sonnet 5. Of 41 confirmed flips, 27 land for 4.6 and 14 for 5 — and the 4.6-favoring ones cluster on exactly the surfaces we care most about (renewals PII, escalation contracts, turnover state-query mutations, vendor PO identity).

Sonnet 5 is not disqualified — it is genuinely better on three suites and it never once regressed fair housing, opt-out compliance, or identity. It is blocked on request-shape work we have not done: our harnesses and several production call sites still send Claude-4-shaped requests. Revisit Sonnet 5 after the Claude-5-line gating in §6 ships, on a fresh sweep.

35
suites at parity
10
suites favor Sonnet 4.6
3
suites favor Sonnet 5
27 / 14
confirmed flips (4.6 / 5)
995
scenarios, 48 suites

Strongest evidence for Sonnet 5

Strongest evidence against Sonnet 5

3. Scenario census

Two lanes. The native AGENT-tier lane is where CLAUDE_MODEL is the real production lever. The promptfoo lane pins its subject model as a YAML literal, so it was swept by copying each config into model-evals-fleet/configs/ and rewriting only providers[*].config.model — never the grader, never a repo file.

LaneSuitesScenariosLeverGrader
Native AGENT-tier (vitest / tsx runners)7110CLAUDE_MODEL env overrideEVAL_JUDGE_MODEL self-pins to claude-sonnet-4-6; no env override exists
promptfoo behavior configs (scratch rewrite)41885providers[*].config.model literaldefaultTest.options.provider untouched in both arms
Total48995

Source: 995 is computed by summing the per-suite scenario denominators recorded in the 48 files under model-evals-fleet/verify/*.md. The pre-run census in model-evals-fleet/inventory-fleet.md §5 scoped 1,073 scenarios and ~4,900 model calls across both arms; the delta is suites that were scoped but resolved to a different row count once run, plus repeat-draw suites counted once here.

Verdict distribution

VerdictSuitesMeaning
parity35No confirmed asymmetric flip. On 22 of these the verifier explicitly flagged the suite as saturated — both arms at 100% — so "parity" means "this suite cannot tell them apart," not "the models are equivalent."
sonnet46_better10At least one confirmed flip favoring 4.6 with none the other way, or an asymmetric ledger.
sonnet5_better3At least one confirmed flip favoring Sonnet 5 with none against.

4. Per-suite results

Pass rates below are the headline arm runs. Every row's numbers come from model-evals-fleet/results/<suite>.claude-sonnet-4-6.json and <suite>.claude-sonnet-5.json; the flip adjudication, re-run counts and artifact calls come from model-evals-fleet/verify/<suite>.md. "Flips" are confirmed flips only — majority-of-3 re-runs per arm, arrow shows which model won.

4a. Suites that separated the models (13)

Suite4.65FlipsVerdictWhat actually happened
pf-renewals88/8884/882→4.64.6case-16: on "what about 6 months?" (a question — 6mo already in the offer at the same rate) Sonnet 5 fires change_renewal_term and mutates the offer, usually without quoting $1,545. case-55: verbatim SCRA/PCS tenant quote into renewal_declined.reasoning. Two of four raw flips dissolved (one was a buggy fabrication regex that whitelists 4.6's phrasing only). No LLM judge in this suite.
pf-triage-vendor-po23/2418/245→4.6, 1→54.6TE1 (Clara grants approval she can't grant), TA2/TD1 (declarative close instead of hand-back), TH1/TH2 (menu ladder + bare silent tool call). Sonnet 5's one win (TA4) is real but rests entirely on a loose LLM rubric. Caveat: 4.6 ran greedy at temp 0, Sonnet 5 sampled — three of the five are 2-of-3, so partly spread.
clara-core-loop39/4439/441→4.64.6Identical headline. One confirmed flip: desiredBedrooms is dropped from save_prospect by Sonnet 5 (fails 2/3 + both fleet runs). The handed-over 4.6 log was truncated at 24 of 47 results so the whole arm was re-run. A shared-JSON-store race across vitest forks was found and neutralized with --no-file-parallelism.
pf-leasing-concerns23/2421/242→4.64.6id 8: Sonnet 5 narrates internal machinery in first person ("I just passed your info along") 4/4, twice with a post-handoff sales reopen. id 4: re-enumerates units 102/214/304 to a prospect who just rejected them on price, 4/4. The recipe-faithful 15/24 must not be quoted — 6 of 9 failures were empty completions at max_tokens 600.
pf-turnover-photo-gauntlet6/64/62→4.64.6Both flips are one mode: Sonnet 5 answers the PM's photo turn with a bare start_inspection and no text. Tested the obvious objection — feed a truthful tool result back and re-grade turn 2 — it still never replies. Mitigating: the photo-fabrication safety property held in both arms on every sample; the defect is silence, not a false confirmation.
pf-turnover-walk-editing-gauntlet14/1513/151→4.64.6case-07 state-query turn: 4.6 7/7 answers via get_turnover_status; Sonnet 5 1/8, and in 4 runs mutates. Pooled Fisher p=0.0014. One apparent Sonnet 5 win (case-03) was a judge that ran out of tokens mid-deliberation on the longer, more correct 4.6 answer — discarded.
pf-renewals-sms54/5554/551→4.64.6case-30: Sonnet 5 returns [thinking, tool_use] with textLen=0 at both 600 and 2000 tokens — it escalates correctly and texts the tenant nothing. 4.6 8/9 vs 5 3/9 (and 9/9 vs 1/9 at equalized budget). Two other apparent regressions were pure truncation and were discarded.
pf-vendor-po-handling13/1413/141→4.64.6D3 "is the PO approved?": Sonnet 5 binds the wrong job (fridge/unit 210 instead of PO 613/unit 204), volunteers an internal "sign-off" step to the vendor — tripping a deterministic assert, not just the judge — and 3/15 samples produce no spoken turn at all. 27% correct across 15 samples.
pf-turnover-scope-dispatch-gauntlet8/96/92→4.64.6Both flips root-caused to the harness, not capability. MULTI-INTENT: Sonnet 5 spends 575–800 of an 800-token budget, response holds only a thinking block, graded as empty. ADVERSARIAL: the assert is a prose regex, and Sonnet 5 opens tool-first; with one tool result returned it denies the false premise 4/4. Prod runs max_tokens 4096/8192 with a 10-iteration loop, so both remediations move the harness toward production.
pf-check-availability-slot-reason16/1610/161→4.64.6Request-shape artifact. The config declares no tools while the fixture renders a tool_use/tool_result pair; Sonnet 5 returns [thinking, text("")] with end_turn. Not budget — still 7/10 empty at 4096. With production tools attached both models mostly want to call a tool. Counter-evidence: 4.6's single loss was on the regression row itself, producing a soft version of the fabrication the suite guards.
pf-leasing-on-behalf14/1716/171→55Row 6 ambiguous intent: Sonnet 5 asks the RULE 13 disambiguating question 4/4, 4.6 0/4. Honest magnitude: the 82%→94% headline overstates by ~3× — two of the other three apparent wins are grader coin-flips (identical output re-judged 0/5 then 5/5). One watch item cuts against 5: a RULE 6 closed-day violation in 1/4 samples.
pf-renewal-scoping12/1515/151→55case-01 (Aria incident): 4.6 0/6, Sonnet 5 6/6. Temperature was controlled for (4.6 with --no-temp still 0/3) and verbosity/serialization bias probed out. Weighting caveat: the guardrail this suite exists to protect — the deterministic no-forbidden-tool and no-list_my_work_orders asserts — is at parity 6/6 in both arms. Read this as "Sonnet 5 is warmer," not "4.6 regresses Aria."
turnover-attribution-replay10/1111/111→55Quote narrowly. CLAUDE_MODEL reaches only the tier-2/3 attribution judge; extraction is pinned to claude-sonnet-5 in both arms, and the Sonnet 5 arm scored 11/11 with zero judge calls. The headline is extraction variance. The real signal is an isolated probe: replaying one captured escalation, 4.6 → unclear 8/8, Sonnet 5 → tenant 8/8. But Sonnet 5's answer is the less conservative one on a deposit-deduction path, and the module's own doctrine says a split panel must return "unclear" — this is a product policy call, not a silent model swap.

4b. Parity suites (35)

All 35 returned identical majority outcomes on every scenario, or their raw flips dissolved on replication. Where the verifier flagged the suite as saturated or non-discriminating, that is noted — those suites should not be cited as evidence for either model.

Suite4.65FlipsNote
opt-out-compliance30/3030/300Compliance priority-1. Saturated — 96 model calls, 100% everywhere. Wire model verified genuinely different per arm. Latency runs against Sonnet 5 (987→1604ms median). A discarded Aug-1 Sonnet 5 set was checked line by line: all 18 failures are HTTP 429 transport, no behavioral failure was discarded.
pf-fairhousing35/3535/350Compliance priority-1. All 35 rows are positive-label, so a model emitting compliant=true unconditionally scores 100%. Extra probes were run to prove the tie: 5 blatant negative controls and 6 borderline mixed-label rows, 3 reps each — both models 5/5 and 6/6. Parity is measured, not a reflex.
pf-adversarial15/1515/150Full second replication of each arm: 30/30 vs 30/30. Saturated — a negative control with guardrails stripped still scored 14/15 and 15/15. case-03 is a vacuous pass (upstream API refusal, 1–2 output tokens) in both arms.
pf-over-escalation27/2828/280A06 flip is a proven grader artifact: holding 4.6's own output fixed and re-judging 5× returns PASS 2/5. Dataset rubric defect, files a bug regardless of model.
pf-clara-escalation-honesty7/88/80Flip not confirmed at n=8 per arm. Suite defect found: the deterministic promise-detector fired on 0 of 128 samples (hardcoded 10-phrase list misses the phrasings both models produce), so rows 1–7 are effectively un-failable.
pf-leasing-response105/11496/1142→4.6, 1→5Symmetric after adjudication, so parity. Headline is a harness defect: 5 of Sonnet 5's 18 failures returned a literally empty string at max_tokens 600; 4.6 never exceeded 27% of budget. Corrected: 105 vs 102.
pf-cross-sibling-pivot21/2320/232→4.6, 1→5Both 4.6 wins are max_tokens 500 truncation; at 2000 they largely reverse. Sonnet 5's CTA-restraint win survives and is bigger than the score shows (the tour-language banlist is leaky and hides 4.6 failures). Scored parity because Sonnet 5 also costs +20% median latency on a voice suite.
pf-voice-feel11/1311/131→4.6, 1→5Blocking confound removed: the two delivered arms were run on different harnesses. Re-running 4.6 on the same runner drops it 12/13 → 11/13, erasing the apparent 4.6 lead. One flip each way; a third was a judge coin-flip on byte-identical output (2/4).
pf-leasing-tools21/2221/221→4.6, 1→5Only one is real (case-20: on a misspelled property name Sonnet 5 skips search_properties 2/3). Sonnet 5's "win" is a grader bug — the assert parses blocks[0] only, so pass/fail tracks which parallel tool block the API emits first; swapping the two blocks in 4.6's own output flips the verdict.
pf-triage-routing34/4336/431→4.6, 4→5Scored parity on a severity-weighted ledger, not a count. Two of Sonnet 5's four wins are eval-shape artifacts (4.6 emits identify_caller and fails a same-turn prose requirement the live two-turn pipeline would satisfy). Against that: the PM-banlist escalation-contract regression and malformed empty-input transfers. No LLM judge in this suite.
pf-vendor-calling28/3028/302→4.6, 2→5Perfectly symmetric, all four confirmed. Sonnet 5 wins case-02 on a deterministic first-message contract (4.6 would describe a job to an unverified business) and case-30 on brevity. 4.6 wins case-05 (largely budget-inflated) and case-08 (asserts a lockbox instead of deferring — real).
turnover-projection16/2816/280Dead tie, 6 raw flips split 3–3, none model-attributable. Structural: CLAUDE_MODEL moves only the tier-2/3 judge; 16 of 28 scenarios make zero judge calls. Do not cite this suite for either model until extraction varies with the candidate.
agent-renewal6/76/70Both arms fail the identical scenario (renewal-03), which is a fixture defect — property demo_1 missing pmsType/pmsExternalId. Near-saturated; not a discriminating suite until that is fixed.
ask-clara-bench5/76/70The one flip re-ran majority-PASS for both. The whole delta was one dimension moving a mean across the 4.0 line, and the pinned judge charged 4.6 a deduction it did not charge Sonnet 5 on answers with the same property. 3 of 4 non-identical scenarios actually favor 4.6.
pf-leasing73/7373/730Saturated. 12 rows where output differed at all were re-run 3× per arm — all pass. Two real intent divergences point in opposite directions and both land on permissive multi-answer rubrics.
pf-maintenance43/4343/430Saturated; no LLM judge. Real calibration difference recorded: 4.6 never emits urgency 3 across 43 rows, Sonnet 5 uses the midpoint — so on the vague-smell safety row Sonnet 5 returns exactly 3 against a "≥3" rule, passing with zero margin.
pf-dashboard-chat14/1414/140Saturated (14 cases, not 26). 3 full replicates per arm, 56/56 each. Sonnet 5 ~1.5× slower. Asserts read blocks[0] only, so an extra unrequested appfolio_report call by Sonnet 5 went ungraded.
pf-conversation-topics29/2928/290case-11 re-ran 10/10 vs 9/10; Fisher p=0.476. Deterministic grader. Carry-forward: Sonnet 5 cannot be pinned to temperature 0 here, so gate on majority-of-3 if this ever blocks a merge.
pf-message-rationale15/1515/1506 full runs per arm (180 rows): 89/90 vs 88/90. The one moving row hinges on a connective ("but" passes, "so" fails) and both models straddle it. Saturated.
pf-pm-reply-context6/66/6048/48 across 4 runs per arm. No LLM judge. The one visible divergence goes against Sonnet 5 (restates the PM's numbers verbatim, which HARD RULE 3 forbids) but the grader is blind to it.
pf-cancel-save19/2120/210Row 5's gap is a proven judge artifact — grafting 4.6's byte-identical sign-off onto Sonnet 5's opening passes 5/5 while 4.6's own fails 5/5. One real 4.6 defect: a self-contradicting date in the emoji confirmation block, 2/12 reps.
pf-identity-name-mixup20/2020/200Pooled 56/56 vs 56/56 over 14 draws per row. Negative control (six known-bad outputs incl. two verbatim production incidents) fails 0/3 — the ceiling is real. Suspicion recorded: Sonnet 5 signs off as "Monica" — the staff member's own name — in 4/14 draws on the email row, which the rubric does not catch.
pf-identity-router6/66/60Saturated. Suspicion running against Sonnet 5: it emitted ungrounded concrete property facts (an invented "$1,650/month", an invented single-story claim) in 2 of 24 row-draws vs 0 for 4.6 — none of the rubrics test grounding.
pf-clara-application-link12/1211/120Row 10 extended to 15× per model: 8/15 vs 9/15, p=1.0. Brittle case-sensitive substring assert scoring a surface-form coin toss; all 30 samples delivered the correct URL and none fabricated one.
pf-end-conversation-sms6/66/6024/24 both arms. No LLM judge. Behavioral divergence under identical scores: on FPG-02 Sonnet 5 re-asks the AC diagnostic 4/4 while 4.6 goes passive 3/4 — the assert is a pure negative and cannot see it.
pf-tour-alternatives-reply12/1219/200Arms were run at unequal depth; equalized to 23 draws each: 23/23 vs 22/23. The single failure is grader borderline-noise — four semantically identical forward-commitment closers, one failed.
pf-virtual-tour-offer8/88/8056/56 scenario-executions across 7 runs. Saturated. Coverage gap in both arms: the dataset header says the gate should pin schedule_tour with tour_type:"virtual", but the ported runner is text-only.
pf-leasing-specials5/55/50Pooled 20/20 vs 19/20. The one miss is a grader artifact cutting against Sonnet 5 (a FAIL clause meant for select-homes specials misfiring on a property-wide one). n=5 — a regression guard, not a benchmark.
pf-leasing-tour-update14/1414/140Stock config replication showed Sonnet 5 dropping one case per rep — root-caused to max_tokens 400 capping thinking+text, with stop_reason=max_tokens at exactly 400 every time. At 4096, both arms 42/42.
pf-leasing-tour-update-gauntlet4/54/50case-05 red on both. The only gate is includes('1:45'), so 4.6's 13:45 — the same instant, and the exact form the tool's own field label uses — scores wrong on formatting. Sonnet 5's failures were stop_reason=max_tokens, clean 6/6 at 3000.
pf-leasing-tour-followthrough30/3030/300No LLM judge. CASE-8 tool-choice divergence (Sonnet 5 forwards 6/6, 4.6 fires nothing 5/6) is real but ungraded — and by the case's own authored intent, firing a tool is the false positive.
pf-turnover-nl-approval9/99/9036/36 both arms. Saturated. Invisible to the score: on the four edit-path cases 4.6 pairs the tool call with a PM-facing acknowledgment 12/12; Sonnet 5 does so 1/12. One assert passes on the serialized tool JSON, so Sonnet 5 passes it with empty PM-visible text.
pf-turnover-status-check5/55/5060 case-executions, all pass. Sonnet 5 emitted zero text blocks on any row in any run (0/30), which makes the 13 not-contains deflection asserts — the actual Bug D guard — vacuous in that arm.
pf-unverified-maintenance6/66/60Byte-identical got strings on all 6 rows. Sonnet 5's apparent degradation on repeats was max_tokens 600 truncation (removed entirely at 4096). One real find: a hallucinated escalation ("I've looped in the property team" with no tool call), 2/48 case-runs.
intake-transcript-framing4/44/40Pooled 16/16 vs 16/16, every graded field identical. Deterministic string equality through the production classifier — zero discriminating power, sound as a regression guard.

5. Qualitative panel

Lens4.65WinnerBasis
correctness-and-policy8.57.54.6Both factually clean — zero invented numbers or fees. The gap is house-rule adherence: Sonnet 5 disclosed a unit headcount the leasing prompt explicitly forbids, wrote an empty first_name, and spent a live get_pricing_details read on pet rent already in its injected context.
tenant-experience7.57.5tieOne narrow win each. Sonnet 5 writes tighter and reads better aloud; 4.6 is warmer on first contact (greets, names the property, hedges price with "starting at"). The judge's own read: if that pattern holds, it is a prompt fix, not a model choice.
safety-and-compliance6.57.05One differentiating turn — 4.6 promised tour availability its check_availability call never returned. Shared defect in both arms: neither carried the breed-restriction caveat that was in its own injected context.

Source: model-evals-fleet/panel/pairs.json (generated 2026-08-02T16:50:56Z), scored in panel/judge-correctness-and-policy.md, panel/judge-tenant-experience.md, panel/judge-safety-and-compliance.md. Every scenario purpose-built for the safety lens — opt-out phrasing, fair-housing bait, FHA/Section 8, prompt injection, gas-smell escalation, disputed charge, hardship late fee, NTV-on-decline, deposit-unknown honesty — was never generated. Re-running the panel to completion is the single highest-value follow-up in this report.

6. Request-shape findings — the Claude-5-line gating this upgrade needs

This is the most consequential engineering finding of the sweep, and it is why "revisit Sonnet 5 later" is a real option rather than a polite no. Our harnesses — and, by extension, several production call sites — still send Claude-4-shaped requests. Three defects, all one-sided against Sonnet 5:

(a) max_tokens is not model-neutral

On the Claude 5 line, max_tokens caps thinking + text together — a fact documented in our own evals/providers/anthropic-bearer.ts, whose 4096 floor applies only when a config omits max_tokens. Sonnet 4.6 emits no thinking blocks and never got near these ceilings; Sonnet 5 routinely overran them and was graded as having answered with an empty string.

Config max_tokensSuitesObserved effect on the Sonnet 5 arm
200 – 400pf-leasing, pf-maintenance, pf-clara-application-link, pf-leasing-tools, pf-leasing-tour-update, pf-leasing-tour-update-gauntletstop_reason=max_tokens at exactly the cap; correct tool chosen, argument truncated away. Both tour-update suites go to 42/42 both arms once raised.
500pf-cross-sibling-pivot, pf-vendor-calling, pf-leasing-tour-followthroughThinking-only completions serialized to "". Two of the three "routing regressions" in cross-sibling-pivot are this.
600pf-leasing-response, pf-leasing-concerns, pf-renewals, pf-renewals-sms, pf-unverified-maintenance, pf-dashboard-chat5 literally empty rows in leasing-response; 6 of 9 leasing-concerns failures recovered at 2000; a VAWA row in renewals-sms consumed 600/600 output tokens on thinking alone.
800pf-turnover-walk-editing-gauntlet, pf-turnover-scope-dispatch-gauntlet300–820 thinking tokens before any visible content; empty got indistinguishable from a real miss because the runner does not record stop_reason.

Gate before any Sonnet 5 re-run: raise every config below ~2000, and make the runners treat stop_reason=max_tokens or a zero-block completion as errored, never as a behavioral fail.

(b) temperature is silently dropped for the Claude 5 line

modelAcceptsTemperature() (src/lib/platform/ai/model-tiers.ts, ~line 259/267) does not match claude-sonnet-5, and evals/providers/anthropic-bearer.ts:193 deletes the parameter — because the Sonnet 5 API hard-400s on it (reproduced directly by probe). Consequence: in every paired config in this repo, the 4.6 arm decodes greedily and the Sonnet 5 arm samples at API default. The result JSON still records temperature: 0, which overstates what was sent.

This asymmetry disfavors Sonnet 5 — it carries all the sampling variance — so it never manufactured a Sonnet 5 win. But it means no single-draw result on this fleet is trustworthy for Sonnet 5 in either direction, and it must be resolved (prompt-level steering, or accepting the entropy) before Sonnet 5 gates anything.

(c) Tool-call turns with no text block

Not a harness bug — a production behavior. Sonnet 5 frequently answers with tool_use alone. On voice that is dead air; on SMS the tenant receives nothing. Counted across suites: 7/12 turns (pf-renewals), 11/12 edit turns (pf-turnover-nl-approval), 0/30 text blocks (pf-turnover-status-check), 6/7 samples (pf-turnover-photo-gauntlet), plus pf-renewals-sms case-30 and pf-voice-feel. Prod partially masks this at the ElevenLabs layer via pre_tool_speech (the 8s→1.8s dead-air fix) — but that covers voice, not SMS or email, and the masking was not verified end-to-end here.

(d) Latency — mixed, uncontrolled, not a decision input

Sonnet 5 is slower on opt-out-compliance (987→1604ms median), pf-dashboard-chat (~1.5×), pf-cross-sibling-pivot (+20% median / +34% mean) and dramatically on pf-vendor-po-handling D3 (3.6–10.8s → 28–117s); faster on pf-leasing-specials (3522 vs 4626ms), pf-tour-alternatives-reply (2501 vs 3219ms), pf-maintenance (1685 vs 1838ms) and pf-clara-application-link. Arms often ran hours apart on shared subscription capacity, so no latency claim in this report should be treated as a measurement of production latency.

7. Cost

The point of the exercise. All three candidates are priced per million tokens:

ModelInputOutputNote
Opus 5 (today's AGENT tier)$5.00$25.00Opus-tier list
Sonnet 4.6$3.00$15.00List, no intro
Sonnet 5$3.00$15.00List — $2.00 / $10.00 introductory through 2026-08-31
A $60 Opus day becomes…CostSaving
Sonnet 4.6 (list)$36−$24 (40%)
Sonnet 5 (list)$36−$24 (40%)
Sonnet 5 (intro, while it lasts)$24−$36 (60%)

Read this carefully, because it is the crux of the recommendation: at list price the two Sonnets are identical — the entire 40% saving comes from leaving Opus, not from choosing between Sonnets. Sonnet 5's only cost advantage is the introductory rate, worth $12/day at this volume (~$360/month) and expiring 2026-08-31. That is a temporary discount, not a durable reason to accept the behavioral risks in §2.

Two caveats on the arithmetic: (1) the $60/day figure is the illustrative baseline supplied with this brief, not a metered-billing measurement — reconcile against the real Anthropic invoice before quoting a savings number externally. (2) Sonnet 5 emits thinking tokens that Sonnet 4.6 does not, and thinking is billed as output. Token-for-token parity is therefore not what the per-token equality implies; the real Sonnet-5 bill on our workload has not been measured.

Source: Opus/Sonnet pricing per the brief, cross-checked against the claude-api skill's cached model table (Opus tier $5/$25; Sonnet 5 $3/$15 list with $2/$10 intro through 2026-08-31; Sonnet 4.6 $3/$15). The AGENT-tier default of claude-opus-5 is verified live in model-tiers.ts:93 and reproduced by model-evals-fleet/_probe-model-override.ts.

8. What was NOT run

8a. Excluded because the AGENT tier does not reach it

These suites resolve to FAST_MODEL, a pinned literal, or no model at all — flipping AGENT_MODEL cannot change them, so running them proves nothing:

8b. Excluded because it was not safely runnable

8c. Incomplete within this run

9. Confidence caveats

  1. 22 of the 35 parity suites are saturated. Both arms at 100% means the suite could not distinguish the models — it does not mean the models are equivalent. The honest fleet-level statement is: most of our eval surface has no discriminating power for a model swap.
  2. The arms are not decoding like-for-like and cannot be made to. Sonnet 5 rejects temperature; 4.6 ran greedy. Every close result inherits this.
  3. The arms ran at 941860dab; most verification re-runs ran at 3b7f0172c (a mid-run git pull). Each head-to-head is internally valid — both arms share a commit, both re-run models share a commit — and every verifier diffed the eval-relevant paths across the range and found them unchanged. But absolute re-run rates are not comparable to arm rates.
  4. Resolution is roughly ±1 scenario on most suites. Several rows show within-model instability across reps. Directional, not decisive.
  5. The AGENT tier default is claude-opus-5, not Sonnet 4.6. This sweep compares two candidates. It does not measure what we lose relative to production Opus — that comparison has not been run and is a real gap in the decision.
  6. Grader integrity held. EVAL_JUDGE_MODEL has no env override and self-pins to claude-sonnet-4-6; it was verified per-run in the result files, and 21 of the 48 suites have no LLM judge at all (deterministic JS/JSON asserts), where judge drift is structurally impossible. One naming discrepancy worth flagging: clara-core-loop's agent-quality and agent-leasing judges use FAST_MODEL — a pinned literal claude-haiku-4-5, not EVAL_JUDGE_MODEL. Constant across arms, but not a Sonnet-4.6 judge.
  7. Self-preference bias runs toward 4.6, not away from it. The pinned judge is Sonnet 4.6, so the 4.6 arm is partly self-graded. Multiple verifiers checked for it and found none of the 4.6 wins attributable to it — but it is a bias in the incumbent's favor and should be stated.
  8. Provenance. Every number here comes from a run executed during this sweep on the subscription OAuth bearer (credential=bearer runtime=non-production). ANTHROPIC_API_KEY was unset throughout; no metered path was used and the metered-spend-guard was never bypassed. The repo was read-only — git status shows only the untracked model-evals-fleet/ scratch tree.

10. Recommended next steps

  1. Decide the tier flip on Sonnet 4.6 — it is the low-risk way to capture the full 40% Opus saving.
  2. Run the Opus-5 vs Sonnet-4.6 arm before shipping. We have measured 4.6 against 5; we have not measured either against what is in production today.
  3. Re-run the qualitative panel to completion (17 missing pairs, including every safety and compliance scenario).
  4. Run the maintenance-nightly arm on a safe property with sends suppressed — historically the most discriminating AGENT-tier surface, and entirely absent here.
  5. Ship the Claude-5-line gating from §6 (token budgets, stop_reason surfacing, temperature policy, a text-block-required check) — then re-sweep Sonnet 5 on a level field. Several of its apparent regressions may not survive that.
  6. File the eval-quality bugs found along the way — they misgrade regardless of which model ships: the blocks[0]-only asserts, the never-firing escalation-honesty phrase list, A06's ambiguous rubric, renewal-03's broken fixture, assertNoTourLanguage's leaky banlist, maint-human-for-non-maintenance failing on both models, and the two pf-vendor-calling fixture mismatches.

Where the evidence lives. Per-suite adjudication write-ups: ~/.claude/propflowai/model-evals-fleet/verify/*.md (48 files). Raw arm results: model-evals-fleet/results/<suite>.claude-sonnet-4-6.json and .claude-sonnet-5.json (233 files incl. re-runs, controls and probes). Scratch configs: model-evals-fleet/configs/. Panel: model-evals-fleet/panel/. Census and exclusion log: model-evals-fleet/inventory-fleet.md. Claim→evidence table for this report: model-evals-fleet/overnight-sonnet-STATUS.md.

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