Models / Anthropic/ Claude Opus 4.8

Claude Opus 4.8

Anthropic · released May 27, 2026

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

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

Our take

Written Aug 3, 2026

Claude Opus 4.8 is Anthropic's flagship reasoning model that can handle up to one million tokens in a single request, with measured top-quartile scores across coding, hard prompts and instruction following. It is available only through hosted channels and sits at a premium price point with no budget tier.

Who should pick it

Choose this for long-document analysis and synthesis at one-million-token scale, or for coding tasks where its measured peak score is strongest. It is also the sensible pick for enterprise procurement via Azure, Google Vertex or Amazon Bedrock if you already hold cloud contracts there. Skip it if cost is a primary constraint, if you need to run models on your own hardware, or if creative writing and mathematics are your main workloads.

The case for it

  • Widest measured capability spread of any tracked model, with its strongest showing in coding.
  • Exceptional context length for long-form work: up to one million tokens in a single request.
  • Consistent top-tier performance across reasoning and instruction tasks.
  • Broad enterprise availability, with nine offers across six providers including major cloud platforms.

The case against it

  • Premium pricing with no budget tier; alternate tiers through some providers are even more expensive.
  • Throughput varies significantly by provider, with a 25% spread from slowest to fastest measured.
  • Creative writing and mathematics lag well behind its own peak performance in coding.
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How good is it?

IntelligencePuzzles, maths, exam questions

4 of 5

Arena Text (overall)14th of 143 · 1474.6

Arena Hard Prompts 7th of 143Arena Maths 21st of 139LiveBench Mathematics 6th of 35 via Max effortLiveBench Reasoning 7th of 35 via Max effortLiveBench Data Analysis 29th of 35 via Max effort

Also on this board: 1483.6 via Thinking (Aug 2, 2026). Read the pair, not the higher one.

CodingWriting and fixing code on its own

4 of 5

Arena Coding7th of 143 · 1527.7

Arena Code (WebDev) 10th of 74LiveBench Coding 7th of 35 via Max effort

Also on this board: 1533.5 via Thinking (Aug 2, 2026). Read the pair, not the higher one.

AgenticPlanning, calling tools, staying on task

3 of 5

Arena Agent (IPS)14th of 36 · 0.033

LiveBench Agentic Coding 13th of 35 via Max effort

Also on this board: 0.094 via Thinking (Jul 28, 2026). Read the pair, not the higher one.

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 Opus 4.8 placed and give it no mark out of five.

Arena Creative Writing 11th of 143 · 1462.1LiveBench Language 15th of 35 · 79.7 via Max effort
Also scored, on boards we give no mark for
Arena Instruction Following 8th of 143LiveBench Instruction Following 5th of 35 via Max effortLiveBench 9th of 35 via Max 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
76.2via Max effortindependentsource ↗
50.5via Max effortindependentsource ↗
81.8via Max effortindependentsource ↗
66via Max effortindependentsource ↗
72via Max effortindependentsource ↗
79.7via Max effortindependentsource ↗
94.3via Max effortindependentsource ↗
89.2via Max effortindependentsource ↗
0.033independentsource ↗
1527.7independentsource ↗
1506independentsource ↗
1472.5independentsource ↗
1474.6independentsource ↗
1538.8independentsource ↗
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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
$5.00 in / $25.00 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$5.00 / $25.001M57 tok/sNoNoConfirmed
OpenRouter$5.00 / $25.001Mnot measuredUnknownUnknownUnknown
Microsoft Azure AIus-east-2$5.00 / $25.001M67 tok/sNoNoUnknown
Microsoft Azure AIglobal$5.00 / $25.001M32 tok/sNoNoUnknown
DeepInfra$5.00 / $25.001Mnot measuredUnknownUnknownUnknown
Google Vertex AIglobal$5.00 / $25.001M63 tok/sNoNoConfirmed
Anthropic$5.00 / $25.001M128K out57 tok/sNoYes30 daysUnknown
Amazon Bedrockeu-west-1$5.50 / $27.501M69 tok/sNoNoConfirmed
Google Vertex AIeurope$5.50 / $27.501M59 tok/sNoNoConfirmed

Across the 9 listings we hold: 7 say they do not train on prompts, 0 say they do and 2 do not say. 4 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
OpenRouter
Microsoft Azure AIus-east-2
Microsoft Azure AIglobal
DeepInfra
Google Vertex AIglobal
Anthropic
Amazon Bedrockeu-west-1
Google Vertex AIeurope

Tool calling: 8 of 9 listings say yes, 1 publishes no parameter list. JSON output: 8 of 9 listings say yes, 1 publishes no parameter list. Strict schema: 6 of 9 listings say yes, 2 say no, 1 publishes no parameter list.

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Models people weigh against Claude Opus 4.8

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When we formed this view

Dates behind this page

Aug 2, 2026BenchmarkScored 1527.7 on Arena Codingleaderboard
Aug 2, 2026BenchmarkScored 1462.1 on Arena Creative Writingleaderboard
Aug 2, 2026BenchmarkScored 1506 on Arena Hard Promptsleaderboard
Aug 2, 2026BenchmarkScored 1477.3 on Arena Instruction Followingleaderboard
Aug 2, 2026BenchmarkScored 1472.5 on Arena Mathsleaderboard
Aug 2, 2026BenchmarkScored 1474.6 on Arena Text (overall)leaderboard
Aug 2, 2026BenchmarkScored 1538.8 on Arena Code (WebDev)leaderboard
Jul 28, 2026BenchmarkScored 0.033 on Arena Agent (IPS)leaderboard
Jul 26, 2026ListedListed on LLMapfirst indexed by our pipeline
Jun 25, 2026BenchmarkScored 76.2 via Max effort on LiveBenchleaderboard

Prices last checked 9d ago

What we do not know about this model yet

  • 1 of 9 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 9 listings do not say whether they train on prompts.
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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-opus-4-8

Machine-readable model card (omc.json) →

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