Claude Sonnet 5.5 arrives faster, at the same price per token

On 2026-09-28, six days after Claude Opus 5.5, Anthropic released Claude Sonnet 5.5 — the second model in the Claude 5.5 family — as a generally available successor to Claude Sonnet 5.

The launch framing in Anthropic's own words: "Introducing Claude Sonnet 5.5, the second model in the Claude 5.5 family. It's a clear upgrade over Claude Sonnet 5, runs 30%+ faster, and costs up to 30% less for most work."

Three things shipped at once:

1. A capability jump, most visible in agentic terminal coding. Anthropic reports 70.6% on Terminal-Bench 4.0 against Sonnet 5's 10.3% — a 60-point move — and 52.1% on Cognition's FrontierCode 1.1 at xhigh effort, plus a 46.2% → 61.6% jump on Chartography (chart recognition without tools) and 57.0% → 80.1% on OSWorld 2.1 (partial score).
2. Unchanged per-token pricing with lower intended cost per task. The rate card is identical to Sonnet 5: $2/MTok input, $10/MTok output, $0.20 cache read. The claimed saving comes entirely from generating fewer tokens per task, not from a price cut.
3. A genuine breaking change for API developers. Thinking is now adaptive and on by default. thinking: {"type": "disabled"} returns a 400 error; the replacement is a new between_tools setting. Four other breaking changes ship alongside it.

Sonnet 5.5 is also the first Sonnet-class model to launch with cyber safeguards, and the first Sonnet to ship with classifiers that block reasoning extraction — both because, in Anthropic's assessment, its cyber capability is now comparable to Opus 5's.

Availability was same-day and broad: Claude API, Amazon Bedrock, Claude Platform on AWS, Google Cloud and Microsoft Foundry, with zero data retention offered. Anthropic committed to not retiring it before 2027-09-28.

FACT — the price card did not move. Sonnet 5.5 costs exactly what Sonnet 5 costs, on every line, per Anthropic's pricing documentation:

Fast mode, in research preview, is listed for Opus 5.5, Opus 5 and Opus 4.8 only — there is no fast-mode line for Sonnet 5.5. US-only inference (inference_geo: "us") applies a 1.1x multiplier, i.e. $2.20 / $11.00 per MTok.

FACT — the tokenizer is unchanged from Sonnet 5. The same text produces the same token counts as Sonnet 5. Against Sonnet 4.6 and earlier the same text produces about 30% more tokens (the newer tokenizer arrived with Opus 4.7).

FACT — the prompt-cache floor dropped. Minimum cacheable prompt is now 512 tokens, down from 1,024 on Sonnet 5, Sonnet 4.6 and Sonnet 4.5. Small and previously uncacheable system prompts become cacheable.

FACT — five breaking changes affect code already on Sonnet 5 (plus one silent behaviour change):

1. thinking: {"type": "disabled"} → 400. Use between_tools.
2. Forced tool use (tool_choice of type any or tool) → 400. Use auto plus strict: true.
3. Thinking blocks are tied to the model and the conversation.
4. On the Claude API and Google Cloud, computer_20251124 → 400; use computer_toolset_20260801. (Amazon Bedrock still accepts computer_20251124.)
5. The advisor tool rejects Opus 4.8, Opus 4.7 and Sonnet 5 as advisors.
6. Silent: text longer than a sentence or two between tool calls now returns as progress-update thinking blocks, empty at the default display: "omitted". No request fails; a UI that streams those notes just goes quiet.

Also returned as 400: non-default temperature, top_p, top_k; manual thinking budgets (budget_tokens); assistant prefill.

FACT — the safeguards surface widened. Sonnet 5.5 can decline a request in five stop_details categories: "cyber", "bio", "frontier_llm", "reasoning_extraction", "general_harms". Server-side fallback (fallbacks: "default", beta, Claude API only) retries "cyber" and "frontier_llm" declines on Sonnet 5; it does not retry "bio", "reasoning_extraction" or "general_harms".

FACT — vision moved to the high-resolution tier. Up to 2,576 pixels on the long edge and 4,784 visual tokens per image, against 1,568 pixels and 1,568 tokens on Sonnet 4.6 and earlier. A 2000×1500 image costs roughly 2.5x the tokens it did on Sonnet 4.6.

FACT — effort became the primary cost knob. Five levels: low, medium, high, xhigh, max, set via output_config.effort. Default is high on the Claude API/Platform, medium in Claude Code and Anthropic's apps. Levels are recalibrated — a level no longer means the same amount of thinking as on Sonnet 5.

Before (Claude Sonnet 5, released June 2026):

• $2 / $10 per MTok input/output.
• Thinking on by default in adaptive form; disabled accepted; manual budget_tokens deprecated.
• Forced tool use accepted (tool_choice any/tool).
• Thinking blocks readable across Sonnet 5, Opus 4.8, Haiku 4.5 and earlier.
• computer_20251124 accepted on all platforms.
• Minimum cacheable prompt 1,024 tokens.
• Artificial Analysis Intelligence Index 38 at max; 82.4 output tokens/second; $5.09 per Index task.
• Anthropic's own launch table put Sonnet 5 at 10.3% on Terminal-Bench 4.0, with no effort level or harness named.

Change (2026-09-28):

• Anthropic released claude-sonnet-5-5 on its own platform plus AWS, Google Cloud and Microsoft Foundry.
• Thinking became adaptive-only; disabled and budget_tokens both return 400.
• Cyber safeguards, distillation classifiers and expanded preserved thinking ship at launch for the first time on a Sonnet model.
• Haiku 5.5 announced as "in the coming weeks" (as of the event date, not yet released).

After (Claude Sonnet 5.5):

• Same rate card: $2 / $10, $0.20 cache read, $2.50 / $4 cache writes, 50% off on Batch.
• between_tools becomes the only way to run without up-front thinking — and only at low, medium or high effort.
• Conversation histories must be append-only; replaying a thinking block after editing earlier history returns 400 for accounts created on or after 2026-08-31 UTC.
• Thinking blocks are account-bound: they only work in the account that produced them, or a linked account.
• Artificial Analysis Intelligence Index 56 at max; 132.2 output tokens/second; $7.67 per Index task.
• Independent harnesses: Zapier AutomationBench 44.75% at $1.14/task (Anthropic reported 44.7%); Cognition FrontierCode 52.1% at xhigh ($1.59/rollout), 49.4% at high ($0.42), 46.2% at max ($20.78); Artificial Analysis's own Terminal-Bench run 63.6% at max against Opus 5.5's 59.6%.

The single most useful before/after line for a budget owner: at max effort Sonnet 5.5 costs ~51% more per task than Sonnet 5 on Artificial Analysis's Index, while at high effort it is meaningfully cheaper. The "30% cheaper" headline is a statement about the middle of the effort range, not a property of the model.

FACT. Sonnet 5.5 keeps Sonnet 5's tokenizer, so cost per task changes purely through how many tokens the model chooses to spend. Two mechanisms drive that:

• Adaptive thinking with a five-level effort dial. The model decides how much to think; output_config.effort steers it. Lower effort means fewer reasoning tokens and faster answers; higher effort means longer reasoning and more self-checking. Anthropic's own framing: "In Claude Code and our apps, the default effort is set to Medium, while the Claude Platform defaults to High."
• Tool-call batching. Anthropic says early testers found that "in head-to-head runs, it batched tool calls together more than Sonnet 5, leading to fewer steps and lower costs." Fewer agentic steps means fewer round trips and fewer accumulated context re-reads.

FACT — what between_tools actually does. It is a distinct third thinking mode, not a rename of disabled. The model does not think before producing its answer — that is why it is described as keeping "up-front thinking off". What it does enable is the model's short progress updates between tool calls, which still come back as thinking blocks. Without tools, the response contains only text, exactly as disabled behaved on Sonnet 5.

Its hard limits, all documented:

• Accepted at low, medium, high. At xhigh or max it returns 400 — to run at those levels you must use adaptive thinking.
• Takes no other field: display, budget_tokens or block_binding alongside it returns 400.
• Effort cannot be changed mid-conversation: a per-message output_config.effort that differs from the level in effect returns 400.
• With server-side fallback, a between_tools request that falls back to Sonnet 5 runs there with thinking: {"type": "disabled"} — i.e. the legacy value still exists, just on the old model.

INTERPRETATION. between_tools is best read as Anthropic's acknowledgement that a mid-tier model does not benefit from long up-front reasoning on every request, while multi-step agents genuinely do benefit from narrating progress mid-loop. It is a capability split, not a compatibility shim.

FACT — why the thinking blocks are now bound. Each thinking block is signed over the conversation that produced it, and carries the producing model and account. Anthropic enforces this by default for accounts created on or after 2026-08-31 00:00 UTC on the Claude API, Bedrock and Google Cloud. A request that replays a block after a change to the system prompt, tools, or an earlier message returns 400. With the thinking-binding-controls-2026-08-01 beta header you can instead opt into prefix_mismatch_behavior: "drop_block"; with that header, drops are reported in a top-level input_transformations array. Anthropic's prescribed fix is to keep conversations append-only and change instructions or tools via mid-conversation system messages instead of edits.

INTERPRETATION — the tier boundary moved. Sonnet 5.5 at $2/$10 now sits within a few points of Opus 5.5 at $4/$20 on knowledge work (GDPval-AA 1,844 vs 1,846; AA-Briefcase 1,811 vs 1,822), on computer use (OSWorld 2.1 partial 80.1% vs 81.8%), and on long-horizon reasoning (HLE with tools 64.5% vs 67.7%). Anthropic's guidance to unsure developers still says start with Opus 5.5, but the economic argument for doing so now applies mainly to open-ended work requiring sustained judgment — not to routine production traffic.

INDEPENDENT EVIDENCE — the speed claim holds and may understate. Artificial Analysis measures Sonnet 5.5 at 132.2 output tokens/second against Sonnet 5's 82.4 tokens/second — about 60% faster, roughly double Anthropic's "30%+ faster". Both figures come from the same independent evaluator on Anthropic's own API, so the comparison is like-for-like. This is the strongest independent confirmation in the story. Note it is an output decode rate, not end-to-end latency: Sonnet 5.5's time-to-first-token is 428.36s at max effort on that same measurement, because adaptive thinking runs before the answer.

INDEPENDENT EVIDENCE — but the cost story is effort-dependent, and partly contradicted. Artificial Analysis's cost per Intelligence Index task:

At max effort Sonnet 5.5 used 192,800 output tokens per Index task against Sonnet 5's 117,800. The Intelligence Index score rose from 38 to 56 over that extra spend. So: the saving is real and large at the settings most production traffic uses, and the headline is defensible; at the top of the effort range the model is materially more expensive, and Anthropic's "up to" is doing real work in that sentence.

INDEPENDENT EVIDENCE — a hands-on test found no saving. DataCamp ran the same build task (a single-file HTML dashboard from FiveThirtyEight's college-majors dataset) against both models. Sonnet 5.5 shipped a working dashboard with small-sample caveats; Sonnet 5 shipped a blank page (broken CDN link for its charting library, unrecoverable error). But cost per run was $0.56 for Sonnet 5.5 vs $0.57 for Sonnet 5 — effectively identical, with Sonnet 5.5 finishing faster. On a single real task, the quality gain was clear and the cost gain was zero. One task is not a benchmark, but it is a direct check of the mechanism the claim depends on, and it did not reproduce it.

COMPANY CLAIM — customer-reported efficiency gains. Anthropic's launch post quotes: Base44 reporting 3.6 iterations per app build against 7.7 with Opus 5; Box reporting workloads 2.4x faster with 12% fewer tokens; Zendesk measuring 20% faster ticket processing; Atlassian saying customers can run Rovo Agents up to 30% faster; Slack reporting roughly 14% fewer output tokens on offline Slackbot evals with unchanged prompts; Epic Games describing multi-hour gameplay-system architecture work over tens of thousands of lines. These are vendor-selected testimonials and are labelled as such.

INTERPRETATION — the benchmark jump is real in direction, softer in magnitude. Two independent harnesses agree the model is dramatically better at terminal agentic work than Sonnet 5 and at least as good as Opus 5.5 there. But the 70.6% figure is Anthropic's own run in Claude Code at max effort, against Opus 5.5's best at xhigh; the system card's own standard errors are ±2.5 and ±2.6 points, and Anthropic claims no statistical significance for the gap (per AI Tools Police's reading of pp.112-113). Artificial Analysis's independent run — different harness, both models at max — gives 63.6% vs 59.6%, roughly 7 points below Anthropic's absolute number while keeping the ordering. The Sonnet 5 baseline of 10.3% is corroborated externally (Artificial Analysis 14.1% at max; Zapier 10.65%), so the size of the improvement is well supported even if the headline figure is harness-specific.

FACT. These are capabilities the model documentation and launch post state directly:

• Agentic terminal work at a mid-tier price. Terminal-Bench 4.0 at 70.6% (Anthropic's run) means multi-step professional tasks inside a command line are now something a $2/$10 model can be trusted to attempt. Independently: 63.6% on a different harness at max, 43.9% at high.
• Cheap merges. Cognition's FrontierCode measures mergeability. At high effort Sonnet 5.5 reaches 49.4% at $0.42 per rollout — matching GPT-6 Sol's best 49.3% at roughly one-fifth the cost per task.
• Real-time SaaS operations. Zapier's AutomationBench puts Sonnet 5.5 at 44.75% for $1.14/task, ahead of Opus 5.5's 42.47% on that leaderboard. Anthropic's own figure of 44.7% was independently confirmed against Zapier's published number.
• Chart and document comprehension at a jump. Chartography 15.6% → 61.6%. High-resolution image input (2,576px / 4,784 tokens) makes real documents and screenshots practical rather than token-expensive.
• Slides, spreadsheets and polished UI code. Anthropic positions Sonnet 5.5 specifically here — "well-scoped everyday tasks, fixing bugs, and creating polished documents, slides, and spreadsheets" — and reports an internal test where two experts judged a 10-slide operating review from quarterly earnings materials as ready to send as-is. DataCamp's hands-on test independently supports the "sharp eye for design" claim on a different artefact.
• Cache small system prompts. The 512-token minimum cache floor makes previously uncacheable prefixes billable at $0.20/MTok.
• Sonnet-tier volume with the Batch discount. $1 input / $5 output on Batch, with up to 300K output tokens via the output-300k-2026-03-24 beta header.

COMPANY CLAIM, not independently verified. "First Sonnet model to beat Pokémon Red working only from screenshots" — a long-horizon and image-understanding proxy. No independent check found.

1. Why did Sonnet 5 score ~10% on Terminal-Bench? Neither of Anthropic's documents explains it. External figures cluster low (Artificial Analysis 14.1% at max, Zapier 10.65%). A 60-point generational jump from a genuinely broken baseline is a different claim from a 60-point jump from a capable baseline.
2. What effort does a given workload actually want? There is no published guidance beyond "start at high". The independent curves disagree about whether max is ever worth it — Cognition says no on FrontierCode, Artificial Analysis says maybe on Terminal-Bench.
3. Can the Cyber Verification Program be extended quickly enough? As of launch it cannot. Open bug #97946 shows the cost of the gap.
4. How much of the "cheaper per task" is just less reasoning at lower effort, and how much is better token allocation? DataCamp's $0.56-vs-$0.57 result and the 192,800-vs-117,800 output-token gap at max both suggest effort choice dominates.
5. Does the speed claim hold outside Anthropic's harness, and at what effort? Artificial Analysis supports the direction; no independent measurement at medium or high was available.
6. Does the reasoning-extraction classifier create false positives on legitimate workloads? It has no server-side fallback, so a false positive is a hard stop.
7. What is the real-world impact of the alignment regressions — the refusal-rate drops and the reported increase in stating incorrect answers — on downstream products?
8. When does Haiku 5.5 land, and at what price? It is the piece that would complete the tier structure against GPT-6 Luna.
9. Will Anthropic publish the cost-per-task methodology behind "up to 30% less"? Absent that, the headline cannot be evaluated outside an effort-controlled comparison.

FACT / already scheduled.

• Claude Haiku 5.5 — promised "in the coming weeks" in the launch post. As of this research (2026-10-04) it had not been released. It is the high-volume, cost-sensitive tier and is the piece that completes the family.
• Expanded Cyber Verification Program — "soon", per both the launch post and the system card ("in the near future"). Open bug anthropics/claude-code#97946 tracks the gap.
• Migration automation — /claude-api migrate in Claude Code for automated model-ID and parameter migration.
• Extended-output beta — up to 300K output tokens on the Message Batches API via output-300k-2026-03-24.
• Compaction on demand — compact-2026-09-04 beta, relevant precisely because Sonnet 5.5 thinking blocks are bound to the conversation.

PREDICTION (clearly labelled, not evidence).

• Independent speed measurements will confirm the direction and probably exceed 30%, since Artificial Analysis already shows ~60%. Expect early published figures to cluster between 40% and 70% depending on effort and harness.
• The first serious cost story will come from teams that ran high and measured their own tokens. Expect reported savings between 20% and 40% at high, near zero at medium on token-heavy tasks, and negative at max. The headline "30%" will survive as a range, not a point.
• Terminal-Bench public leaderboards will fill in. Expect independent scores for Sonnet 5.5 in the high-50s to mid-60s rather than 70.6%, and expect the Opus 5.5 comparison to be closer than Anthropic's 4.2-point table implies once run at equal effort.
• The max-effort cost inversion — Sonnet 5.5 costing more per task than Opus 5.5 — will be widely reported within weeks and will become a standard caveat quoted alongside the launch numbers.
• CVP complaints will persist until the programme extends, and pressure for tiered cyber access at mid-tier will become a standing procurement requirement.
• Sonnet 5 will remain available as the fallback target for some time, which conveniently preserves an A/B path — but it also means quality silently degrades on flagged requests.

FACT — verification status as of 2026-10-04. Zapier's AutomationBench leaderboard 1.0.6 now lists Claude Sonnet 5.5 (default fallbacks, Max) at 44.75% for $1.14/task. Cognition's FrontierCode changelog shows Sonnet 5.5 added 2026-09-28 and GPT-6.1 Sol added 2026-09-29. Artificial Analysis now carries a speed figure for Sonnet 5.5 that was absent on launch day.

The headline is two-thirds right, and the wrong third is the part your bill depends on.

Claude Sonnet 5.5 is a genuinely large step up from Sonnet 5 on agentic work, and the speed claim is now independently verified — Artificial Analysis measures 132.2 output tokens per second against Sonnet 5's 82.4, roughly double Anthropic's conservative "30%+ faster". The Terminal-Bench jump is corroborated in direction by a second harness and the low Sonnet 5 baseline is corroborated by two others, so a 60-point improvement in terminal agentic capability is real even if 70.6% is Anthropic's own harness talking.

The cost claim is where the story needs care. The per-token price did not move — $2 and $10, identical to Sonnet 5. The entire saving is a promise about token efficiency, and it is qualified twice by Anthropic ("up to", "for most work") for good reason. Independent arithmetic on Artificial Analysis's Index: about 40% cheaper per task at high, about 41% at medium, about 19% at low, roughly 5% at xhigh — and about 51% more expensive at max. DataCamp's hands-on build found no cost difference at all ($0.56 vs $0.57) alongside a clear quality win. The saving is real in the middle of the range and absent at both ends.

Two things are more important than either headline. First, the launch table's numbers are max-effort numbers, and max is the worst value in the range on at least one independent benchmark — Cognition's FrontierCode scores Sonnet 5.5 lower at max than at xhigh, at roughly thirteen times the cost per rollout. Teams that adopt on the benchmark table and default to a high effort setting will not get the economics the announcement implies.

Second, the release carries five 400-error breaking changes plus one silent response-shape change, and one of them is not a rename at all. between_tools is a genuinely new thinking mode — up-front reasoning off, progress updates between tool calls on — with hard limits: it works only at low/medium/high, cannot be combined with a display or budget_tokens field, and freezes effort for the life of the conversation. It is mandatory only for code that explicitly sends disabled, but the broader change is bigger: histories must now be append-only, enforced by default for accounts created on or after 2026-08-31 UTC.

And a quieter theme runs underneath all of it. This is the first Sonnet to ship with cyber safeguards and reasoning-extraction classifiers. Anthropic's own safety card reportedly shows Sonnet 5.5 refusing malicious requests less often than Sonnet 5 (85.2% vs 87.9% in Claude Code), while authorised defenders in the paid Cyber Verification Program cannot use either new flagship model yet. The safeguards are real; so is the friction they create, and it lands unevenly.

The right summary for a reader: a fast, cheap, much more capable mid-tier model with a mandatory migration, a headline cost saving that only exists in the middle of its effort range, and a safety perimeter that arrived a step ahead of the access programme meant to serve the people it inconveniences. Migrate, set effort deliberately, and measure your own tokens before you believe the number.