Models / Anthropic/ Claude Opus 4.6

Claude Opus 4.6

Anthropic · released Feb 4, 2026

Input: text, images and documents. Output: text.InputOutput
Type
Closed
Input
$5.00
Output
$25.00
Cached
$0.50

List price · per 1M tokens · Anthropic at 1M context · machine-readable source ↗

Our take

Written Sep 5, 2026

Claude Opus 4.6 is Anthropic's flagship reasoning model that can handle up to one million tokens in a single request. It excels at mathematics, reasoning and coding tasks, though it costs noticeably more than most alternatives and shows weaker results on agentic work.

Who should pick it

Pick this for long-document analysis at one million tokens, mathematics and reasoning workloads, or coding and web development where measured scores are strong. Use it when recovery from errors in agentic sessions matters. Skip it if you need budget-friendly inference, strong instruction-following, or reliable agentic task completion and tool use.

The case for it

  • Exceptional measured mathematics and reasoning performance: 89.32% and 88.67% on LiveBench.
  • Strong coding across multiple evaluation types, including 75.6% on SWE-bench Verified.
  • One-million-token request limit — four times the 256K common on many frontier models.
  • Highest measured throughput on Google Vertex at 43 tps, versus 20–39 tps elsewhere.

The case against it

  • Agentic coding and instruction following lag far behind its own mathematics and reasoning peaks.
  • Premium pricing with no budget tier; costs noticeably more than most alternatives.
  • Throughput varies more than twofold across hosts at identical pricing.
00

How good is it?

A general-purpose assistant for everyday questions, writing, coding and multi-step tasks.

Good at
  • answering everyday questionsArena Text (overall) · 4th of 168
  • drafting, rewriting and editing textArena Creative Writing · 8th of 168
  • writing and completing codeArena Coding · 2nd of 168
  • carrying out multi-step work for youArena Agent · 9th of 55
  • calling tools to carry out requestsArena Agent · Tool use · 2nd of 55
  • changing course when given new instructionsArena Agent · Steerability · 11th of 55
  • getting back on track after a step failsArena Agent · Recovery · 4th of 55

EverydayGeneral questions and everyday reasoning

4.5 of 5

Arena Text (overall)4th of 168 · 1498

Arena Hard Prompts 3rd of 168Arena Maths 8th of 163LiveBench Reasoning 17th of 58LiveBench Mathematics 31st of 58LiveBench Data Analysis 46th of 58

Also on this board: 1505 (Sep 25, 2026), 1505 (Aug 10, 2026). Read the pair, not the higher one.

CodingWriting and fixing code on its own

5 of 5

Arena Coding2nd of 168 · 1548

Arena Code (WebDev) 29th of 95LiveBench Coding 28th of 58

Also on this board: 1551 (Sep 25, 2026), 1552 (Aug 10, 2026). Read the pair, not the higher one.

AgenticPlanning, calling tools, staying on task

3 of 5

Arena Agent9th of 55 · 0.047

LiveBench Agentic Coding 39th of 58SWE-bench Verified 3rd of 42

WritingDrafting and rewriting prose

4 of 5

Arena Creative Writing8th of 168 · 1478

LiveBench Language 17th of 58

Also on this board: 1501 (Sep 25, 2026), 1500 (Aug 10, 2026). Read the pair, not the higher one.

How it behaves in an agent loop
Tool usereaches for the right one, and does not invent one2nd of 55
Steerabilitydoes what it was asked, and changes course when told11th of 55
Recoverygets back on track after a command fails4th of 55
Task outcomefinishes what the session set out to do22nd of 55

Placings on Arena's agent boards, from live sessions people ran themselves. A model can lead on one of these and sit mid-field on the others.

Other boards it appears on
Arena Instruction Following 3rd of 168LiveBench 34th of 58LiveBench Instruction Following 41st of 58Arena Agent · Tool use 2nd of 55Arena Agent · Recovery 4th of 55Arena Agent · Steerability 11th of 55Arena Agent · Task outcome 22nd of 55

Boards this model appears on that none of the ratings above are built on.

Every published score for this model21 scoresEvery figure we hold, from 21 boards, with who ran it and a link to the source — including the boards no rating above is built on.
LiveBenchreasoning
74.52source ↗
48.99source ↗
78.18source ↗
69.89source ↗
63.31source ↗
83.27source ↗
89.32source ↗
88.67source ↗
0.047source ↗
0.086source ↗
0.046source ↗
0.025source ↗
0.008source ↗
1548source ↗
1478source ↗
1527source ↗
1507source ↗
1498source ↗
1537source ↗
75.6source ↗
01

Where to rent it

Prices checked between 57 min and 60 min ago — each listing carries its own date.

Cheapest published offer

Anthropic, direct

The lab is also the cheapest we hold. The strip above and this offer are the same one, so nothing on this page undercuts Anthropic on 1M of context.

per 1M tokens
$5.00 in / $25.00 out
Context served
1M
Throughput
~35 tok/s
Current provider offers with price, context and prompt-privacy answers
ProviderIn / out per 1M tokensContextThroughputTrains on promptsLogs promptsZero retention
Google Vertex AIglobalThrough OpenRouter$5.00 / $25.00checked 59 min ago1M128K max reply35 tok/sNoNoConfirmed
Microsoft Azure AIglobalThrough OpenRouter$5.00 / $25.00checked 59 min ago1M128K max reply33 tok/sNoNoUnknown
Claude Platform on AWSThrough OpenRouter$5.00 / $25.00checked 59 min ago1M128K max reply36 tok/sNoYes30 daysUnknown
OpenRouterOpenRouter's own listing$5.00 / $25.00checked 60 min ago1Mnot measuredUnknownUnknownUnknown
AnthropicDirect$5.00 / $25.00checked 57 min ago1M128K max reply35 tok/sNoYes30 daysUnknown
Amazon BedrockThrough OpenRouter$5.00 / $25.00checked 59 min ago1M128K max reply34 tok/sNoNoConfirmed
Google Vertex AIeuropeThrough OpenRouter$5.50 / $27.50checked 59 min ago1M128K max reply50 tok/sNoNoConfirmed

Across the 7 listings we hold: 6 say they do not train on prompts, 0 say they do and 1 does not say. 3 appear in the zero-retention registry we check; the rest are unknown to us.

What each host's API supports

From the parameter list each endpoint publishes. Streaming is omitted: nothing we hold reports it, for any model.

API features per host
ProviderTool callingJSON outputStrict schema
Google Vertex AIglobalThrough OpenRouter✓✓✓
Microsoft Azure AIglobalThrough OpenRouter✓✓✓
Claude Platform on AWSThrough OpenRouter✓✓✓
OpenRouterOpenRouter's own listing✓✓✓
AnthropicDirect✓✓✓
Amazon BedrockThrough OpenRouter✓✓✓
Google Vertex AIeuropeThrough OpenRouter✓✓✓

Tool calling: 7 of 7 listings say yes. JSON output: 7 of 7 listings say yes. Strict schema: 7 of 7 listings say yes.

02

Models people weigh against Claude Opus 4.6

03

When we formed this view

Recent changes

Sep 25, 2026BenchmarkScored 1548 on Arena Coding
What movedleaderboard
Sep 25, 2026BenchmarkScored 1478 on Arena Creative Writing
What movedleaderboard
Sep 25, 2026BenchmarkScored 1527 on Arena Hard Prompts
What movedleaderboard
Sep 25, 2026BenchmarkScored 1500 on Arena Instruction Following
What movedleaderboard
Sep 25, 2026BenchmarkScored 1507 on Arena Maths
What movedleaderboard
Sep 25, 2026BenchmarkScored 1498 on Arena Text (overall)
What movedleaderboard
Sep 25, 2026BenchmarkScored 1537 on Arena Code (WebDev)
What movedleaderboard
Sep 5, 2026BenchmarkScored 0.047 on Arena Agent
What movedleaderboard
Sep 5, 2026BenchmarkScored 0.086 on Arena Agent · Recovery
What movedleaderboard
Sep 5, 2026BenchmarkScored 0.046 on Arena Agent · Steerability
What movedleaderboard

Each date is the day we first saw the change, or the day the maker announced it.

What we do not know about this model yet

  • Nothing we hold says whether an endpoint streams, so we do not show it either way.
  • 1 of 7 listings does not say whether it trains on prompts.
  • We hold no batch or off-peak rate for any of its listings.
04

Licence and identifiers

What the licence allowsWe hold no licence record for this model. Inside are the identifiers you need to pull it — its Hugging Face repo where we have one, our slug and a machine-readable card.

Licence

We hold no licence record for this model, and no record of published weights either — so we can neither summarise its terms nor point you at the weights.

Identifiers

Takes in, gives back
Text, images and documents in, text out
Catalogue slug
anthropic-claude-opus-4-6

Machine-readable model card (omc.json) →

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