Models / Anthropic/ Claude Sonnet 4.6

Claude Sonnet 4.6

Anthropic · released Feb 17, 2026

Input: text, images and documents. Output: text.InputOutput
Type
Proprietary
Input
$3.00
Output
$15.00
Cached
$0.30

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

Our take

Written Aug 3, 2026

Claude Sonnet 4.6 is a proprietary text-and-image model from Anthropic that can handle up to one million tokens in a single request. It scores strongly on coding and instruction-following leaderboards, though every tracked host charges a premium rate with no budget tier available.

Who should pick it

Choose this for long-document analysis or codebase work at one million tokens, where few alternatives match the context length. It is the sensible pick for coding and web-development tasks where measured leaderboard scores top 1520, or for instruction-following workflows that demand high precision. Skip it if cost is a primary constraint, if you need to run the model on your own hardware, or if creative writing quality is the deciding factor.

The case for it

  • Exceptional context length for long-document and codebase work, at one million tokens.
  • Strong measured performance on coding tasks, with Arena Coding and WebDev scores above 1520.
  • Stable leaderboard presence over time, with variation under one point across tracked dates.
  • Multiple throughput tiers on major clouds, from 13 to 45 tokens per second depending on provider and tier.

The case against it

  • Premium pricing with no budget tier: every tracked host charges the same rate, so there is no price competition.
  • Creative writing lags well behind its coding peak, a gap of over 75 points on the same leaderboard.
  • Throughput is unmeasured on some channels and spans a wide range where it is recorded, from 25 to 45 tokens per second on one provider alone.
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How good is it?

IntelligencePuzzles, maths, exam questions

4 of 5

Arena Text (overall)16th of 143 · 1471.7

Arena Hard Prompts 10th of 143Arena Maths 27th of 139LiveBench Data Analysis 11th of 35 via Thinking Auto Medium effortLiveBench Reasoning 16th of 35 via Thinking Auto Medium effortLiveBench Mathematics 22nd of 35 via Thinking Auto Medium effort

CodingWriting and fixing code on its own

4 of 5

Arena Coding9th of 143 · 1526.9

Arena Code (WebDev) 15th of 74LiveBench Coding 13th of 35 via Thinking Auto Medium effort

AgenticPlanning, calling tools, staying on task

2.5 of 5

Arena Agent (IPS)15th of 36 · 0.032

LiveBench Agentic Coding 27th of 35 via Thinking Auto Medium effort

WritingWe do not rate this

Scored, not ratedThe placings are on the right.

Two boards come close and neither tests writing: Arena Creative Writing asks people which of two replies they prefer, and LiveBench Language tests whether a model understood a passage. So we show where Claude Sonnet 4.6 placed and give it no mark out of five.

Arena Creative Writing 16th of 143 · 1451.4LiveBench Language 21st of 35 · 76.1 via Thinking Auto Medium effort
Also scored, on boards we give no mark for
Arena Instruction Following 9th of 143LiveBench 21st of 35 via Thinking Auto Medium effortLiveBench Instruction Following 23rd of 35 via Thinking Auto Medium effort

These tests check whether a model follows instructions — a precondition for all the work above, but not a measure of how well that work is done, which is why they get no rating.

Every published score for this model16 scoresEvery figure we hold, from 16 boards, with who ran it and a link to the source — including the boards no rating above is built on.
LiveBenchreasoning
73via Thinking Auto Medium effortindependentsource ↗
42.6via Thinking Auto Medium effortindependentsource ↗
79.3via Thinking Auto Medium effortindependentsource ↗
78via Thinking Auto Medium effortindependentsource ↗
63.2via Thinking Auto Medium effortindependentsource ↗
76.1via Thinking Auto Medium effortindependentsource ↗
87via Thinking Auto Medium effortindependentsource ↗
84.8via Thinking Auto Medium effortindependentsource ↗
0.032independentsource ↗
1526.9independentsource ↗
1503independentsource ↗
1463.8independentsource ↗
1471.7independentsource ↗
1522.6independentsource ↗
01

Or rent it from someone else

Cheapest published offer

Why this differs from the header. The strip above quotes Anthropic's own list price. This is the cheapest live offer at the widest standard context we hold, whoever is serving it — a reseller undercutting a lab is ordinary commerce, not an error.

per 1M tokens
$3.00 in / $15.00 out
Context served
1M
Throughput
Not measured
Current provider offers with price, context and prompt-privacy answers
ProviderIn / out per 1M tokensContextThroughputTrains on promptsLogs promptsZero retention
Amazon Bedrock$3.00 / $15.00200K48 tok/sNoNoConfirmed
DeepInfra$3.00 / $15.001Mnot measuredUnknownUnknownUnknown
Microsoft Azure AIus-east-2$3.00 / $15.001M13 tok/sNoNoUnknown
Microsoft Azure AIglobal$3.00 / $15.001M32 tok/sNoNoUnknown
Google Vertex AIglobal$3.00 / $15.001M41 tok/sNoNoConfirmed
Google Vertex AIeurope$3.00 / $15.001M45 tok/sNoNoConfirmed
Google Vertex AI$3.00 / $15.001M25 tok/sNoNoConfirmed
OpenRouter$3.00 / $15.001Mnot measuredUnknownUnknownUnknown
Anthropic$3.00 / $15.001M64K out38 tok/sNoYes30 daysUnknown
Amazon Bedrockglobal$3.00 / $15.001M39 tok/sNoNoConfirmed
Amazon Bedrockeu-west-1$3.00 / $15.00200K53 tok/sNoNoConfirmed
Google Vertex AIus-east5$3.30 / $16.501M19 tok/sNoNoConfirmed

Across the 12 listings we hold: 10 say they do not train on prompts, 0 say they do and 2 do not say. 7 appear in the zero-retention registry we check; the rest are unknown to us rather than confirmed either way.

What each host's API supports

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

Supported
Not supported
Not published
host gave no parameter list
API features per host
ProviderTool callingJSON outputStrict schema
Amazon Bedrock
DeepInfra
Microsoft Azure AIus-east-2
Microsoft Azure AIglobal
Google Vertex AIglobal
Google Vertex AIeurope
Google Vertex AI
OpenRouter
Anthropic
Amazon Bedrockglobal
Amazon Bedrockeu-west-1
Google Vertex AIus-east5

Tool calling: 11 of 12 listings say yes, 1 publishes no parameter list. JSON output: 5 of 12 listings say yes, 6 say no, 1 publishes no parameter list. Strict schema: 4 of 12 listings say yes, 7 say no, 1 publishes no parameter list.

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Models people weigh against Claude Sonnet 4.6

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When we formed this view

Dates behind this page

Aug 2, 2026BenchmarkScored 1526.9 on Arena Codingleaderboard
Aug 2, 2026BenchmarkScored 1451.4 on Arena Creative Writingleaderboard
Aug 2, 2026BenchmarkScored 1503 on Arena Hard Promptsleaderboard
Aug 2, 2026BenchmarkScored 1477.1 on Arena Instruction Followingleaderboard
Aug 2, 2026BenchmarkScored 1463.8 on Arena Mathsleaderboard
Aug 2, 2026BenchmarkScored 1471.7 on Arena Text (overall)leaderboard
Aug 2, 2026BenchmarkScored 1522.6 on Arena Code (WebDev)leaderboard
Jul 28, 2026BenchmarkScored 0.032 on Arena Agent (IPS)leaderboard
Jul 26, 2026ListedListed on LLMapfirst indexed by our pipeline
Jun 25, 2026BenchmarkScored 73 via Thinking Auto Medium effort on LiveBenchleaderboard

Prices last checked 9d ago

What we do not know about this model yet

  • 1 of 12 listings publish no parameter list, so what their API accepts is unknown to us.
  • Nothing we hold says whether an endpoint streams, so we do not show it either way.
  • 2 of 12 listings do not say whether they train on prompts.
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

Commercial API terms. We hold no licence record for this model, so there is nothing to summarise here.

Identifiers

Modality record
text+image+file->text
Catalogue slug
anthropic-claude-sonnet-4-6

Machine-readable model card (omc.json) →

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