Claude Opus 4.8
Claude Opus 4.8 shipped on May 28, 2026, presented by Anthropic as its most capable model, and twelve days later Fable 5 was already above it; Opus 5 followed on Jul 24. It is now legacy: it costs US$ 5 per million input tokens and US$ 25 per million output, against US$ 4 and US$ 20 for Opus 5.5, which the documentation says to migrate to, and it will not be retired before May 28, 2027. It still has a role no other model has: it is the model that answers when Fable 5, Fable 5.1, Opus 5 and Opus 5.5 block a cybersecurity request.
Claude Opus 4.8 in official numbers
Data published by the maker in its documentation and announcement. The source of each item is at the end of the page.
- Maker
- Anthropic
- API identifier
claude-opus-4-8- Release
- May 28, 2026
- Status
- legacy; the documentation says to migrate to Opus 5.5
- Input
- US$ 5 per million tokens
- Output
- US$ 25 per million tokens
- Cache read
- US$ 0.50 per million (10% of input; US$ 0.20 on Opus 5.5)
- Cache write
- US$ 6.25 (5 minutes) or US$ 10 (1 hour)
- Batch API
- US$ 2.50 input and US$ 12.50 output
- Fast mode
- US$ 10 and US$ 50, up to 2.5 times faster, Anthropic API only
- Context window
- 1 million tokens, no surcharge
- Max output
- 128 thousand tokens (300 thousand in batch, beta)
- Reliable knowledge
- through January 2026
- Reasoning
- adaptive, off unless the request turns it on; default effort high
- Cache minimum
- 1,024 tokens (512 on current models)
- Where it runs
- Anthropic API, Amazon Bedrock, Google Cloud, Microsoft Foundry and Claude Platform on AWS
- Retention and capacity
- available with zero data retention; supports Priority Tier
- Retirement
- not before May 28, 2027
Where Claude Opus 4.8 does well, where it falls behind and who it is for
Where it does well
- Coding: 69.2% on SWE-Bench Pro at launch, against 64.3% for Opus 4.7, 58.6% for GPT-5.5 and 54.2% for Gemini 3.1 Pro.
- Office work: 1,890 on GDPval-AA, against 1,769 for GPT-5.5 and 1,753 for Opus 4.7.
- Financial analysis: 53.9% on Finance Agent v2, ahead of GPT-5.5 (51.8%) and Opus 4.7 (51.5%).
- Honesty: according to Anthropic, around four times less likely than Opus 4.7 to let flaws in code it wrote pass unremarked.
- Predictable in the API: it follows prompts literally, especially at low effort, and only thinks when the request turns thinking on, which helps structured extraction and pipelines.
Where it falls behind
- Terminal: 74.6% on Terminal-Bench 2.1, behind GPT-5.5's 78.2% in its own launch table.
- Previous generation: at the Opus 5 launch, it scored 21.1% on Frontier-Bench v0.1 against 43.3%, and 1.5% on ARC-AGI-3 against 30.2%, at the same price per token.
- Prompt injection: the system card says it is somewhat less robust than Opus 4.7 in several agentic contexts; the safeguards close the gap in practice.
- Effort-sensitive: Anthropic says effort matters more for it than for any prior Opus and that, at low, there is a risk of under-thinking on moderately complex tasks.
- Cache: it only caches prompts from 1,024 tokens, against 512 on current models, and rereads for US$ 0.50, against US$ 0.20 on Opus 5.5.
Who it makes sense for
- Fallback for refusals: it is where newer Fable and Opus models send blocked cybersecurity requests, billed at its own rates.
- Accounts with a Priority Tier contract, which Opus 4.8 supports and Opus 5.5 does not.
- Pipelines that run without thinking, force a tool with
tool_choiceor usecomputer_20251124: all of that works on 4.8 and breaks on Opus 5.5. - Systems validated on it that need time to rerun tests: it will not be retired before May 28, 2027, with at least 60 days' notice.
When to pick another model
- New projects: the documentation says to start with Opus 5.5, at US$ 4 and US$ 20 per million tokens.
- Long agent work: at the same price, Opus 5 more than doubled its score on Frontier-Bench v0.1 at a lower cost per task.
- Fast mode: Opus 5.5's costs US$ 8 and US$ 40, against US$ 10 and US$ 50.
- Tasks that need recent knowledge: its reliable cutoff is January 2026; Opus 5.5's is June 2026.
What Anthropic published at launch
Opus 4.8 arrived on May 28, 2026 as an update to Opus 4.7 at the same price, and Anthropic itself called it a modest but tangible improvement. It came with effort control in Claude.ai, dynamic workflows in Claude Code, with hundreds of parallel subagents, and a fast mode three times cheaper than on previous models.
Two caveats from Anthropic itself: on Terminal-Bench 2.1, all models ran on the public Terminus-2 harness, and GPT-5.5 scores 83.4% with the Codex CLI; on OSWorld-Verified, the table shows 82.8% for Opus 4.7, but the footnote says 82.3%.
| Opus 4.8 Anthropic | Opus 4.7 Anthropic | GPT-5.5 OpenAI | Gemini 3.1 Pro | |
|---|---|---|---|---|
| SWE-Bench Pro coding |
69.2% | 64.3% | 58.6% | 54.2% |
| Terminal-Bench 2.1 terminal coding |
74.6% | 66.1% | 78.2% | 70.3% |
| Humanity's Last Exam without tools |
49.8% | 46.9% | 41.4% | 44.4% |
| Humanity's Last Exam with tools |
57.9% | 54.7% | 52.2% | 51.4% |
| OSWorld-Verified computer use |
83.4% | 82.8% | 78.7% | 76.2% |
| GDPval-AA office work, Elo |
1,890 | 1,753 | 1,769 | 1,314 |
| Finance Agent v2 financial analysis |
53.9% | 51.5% | 51.8% | 43.0% |
Figures from the Claude Opus 4.8 announcement, checked against table 8.1.A of the system card (max effort, averaged over 5 trials). The dot marks the best in each row.
Anthropic's fallback model
Opus 4.8 picked up a second job. When Fable 5's classifiers block a cybersecurity request, the answer comes from Opus 4.8, and the user is told. Opus 5 does the same in Claude.ai, Claude Code and Cowork, and Opus 5.5 reroutes most cybersecurity tasks to it. In Fable 5.1's tests, blocked cyber tasks were also completed by Opus 4.8.
On the API, the fallback is optional: the fallbacks parameter (beta) reruns a refused request on another model, and the documentation's example uses claude-opus-4-8. That part is billed at the fallback model's rates, so if you configure it you may see Opus 4.8 on your bill even after migrating.
Is Opus 4.8 still worth using in 2026?
As your main model, no. At the same price per token, Opus 5 already beat it comfortably at its own launch, and Opus 5.5 costs less than both. The documentation says to migrate straight to Opus 5.5.
There are three reasons to keep it longer: the fallback role, Priority Tier contracts and integrations that depend on running without thinking or forcing a tool. Anthropic guarantees it will not be retired before May 28, 2027 on the platforms it operates and gives at least 60 days' notice; Amazon Bedrock and Google Cloud set their own dates.
| Opus 4.8 legacy | Opus 5 legacy | Opus 5.5 current | |
|---|---|---|---|
| Input | US$ 5 | US$ 5 | US$ 4 |
| Output | US$ 25 | US$ 25 | US$ 20 |
| Cache read | US$ 0.50 | US$ 0.50 | US$ 0.20 |
| Fast mode | US$ 10 and US$ 50 | US$ 10 and US$ 50 | US$ 8 and US$ 40 |
| Reasoning when not requested |
off | on | always on |
| Default effort | high | high | medium |
| Cache minimum | 1,024 tokens | 512 tokens | 512 tokens |
| Reliable knowledge | January 2026 | May 2026 | June 2026 |
| Retirement not before |
May 28, 2027 | Jul 24, 2027 | Sep 22, 2027 |
Anthropic documentation: pricing, each model's page, migration guide and model deprecations, checked on Oct 1, 2026.
What changes when you migrate to Opus 5.5
The migration guide treats Opus 4.8 almost like Opus 5: both accept thinking turned off, forced tool use and the old computer use tool, and both default to high effort. All of that changes on Opus 5.5:
- Thinking by default: on Opus 4.8, a request without a
thinkingfield runs without thinking; on Opus 5.5, it always thinks. Thinking tokens are billed as output, so the same work can produce more output. - Turning thinking off or setting a manual budget returns a 400 error; the control is effort, which defaults to medium. At xhigh or max, start
max_tokensat 64 thousand. - Forced tool use (
anyortool) andcomputer_20251124on the API and Google Cloud now return a 400 error. - Text between tool calls now arrives in thinking blocks, empty by default.
- Caching starts at 512 tokens, with no code change, and Priority Tier goes away.
Examples of using Claude Opus 4.8
A security tool runs on Opus 5.5 with fallbacks in default mode. When the classifier blocks a cybersecurity request, the API reruns it on Opus 4.8, and the response names the model that served it, billed at its rates.
A pipeline reads contracts and returns fields through forced tool use, without thinking, to stay fast and predictable. It works on Opus 4.8. To move to Opus 5.5, you need to replace forced tool use with auto and strict tools and accept thinking, controlled by effort.
Pick ten real tasks and run them on Opus 4.8 at xhigh, Anthropic's recommendation for coding, and on Opus 5.5 at medium. Compare accuracy, output tokens and cost per task, because always-on thinking changes the bill.
Where Claude Opus 4.8 stands out and where it falls behind, by the numbers
Claude Opus 4.8 has published results on 38 tests compiled by Epoch AI. The yardstick here is its generation: its position among the models released between Aug 31, 2025 and Aug 26, 2026 that took the same test. Against the whole archive, which includes 2023 models, a recent release lands near the top of almost everything, and that says nothing.
Where it stands out
Tests where it sits in the top third of its own generation.
Where it falls behind
Tests where it sits in the bottom half of its own generation.
See all 38 tests, one by one
| Test | Score | In its generation | Overall | Test record |
|---|---|---|---|---|
| GPQA Diamond | 91.0% | #21 / 72 (tied with 1) | #28 / 173 | 96.4% Gemini 4 Argon |
| AIME 2024 and 2025 (OTIS) | 98.3% | #10 / 72 (tied with 1) | #22 / 168 | 100.0% GPT-5.5 |
| Dtbench | 94.9% | #11 / 67 | #18 / 148 | 98.9% Claude Opus 5.5 |
| Lmca | 57.51 | #4 / 65 | #8 / 121 | 68.23 Claude Opus 5.5 |
| CritPt | 20.9% | #10 / 65 (tied with 1) | #21 / 112 | 32.3% GPT-5.6 Sol |
| WeirdML | 82.9% | #5 / 57 | #8 / 112 | 93.6% GPT-6 Astra |
| SciCode | 53.5% | #19 / 61 (tied with 1) | #35 / 104 | 66.9% Claude Opus 5.5 |
| Frontiermath Tiers 1 3 V2 | 80.0% | #9 / 55 | #17 / 86 | 93.7% GPT-6 Astra |
| ARC-AGI 2 | 72.1% | #12 / 46 (tied with 1) | #19 / 83 | 95.0% GPT-6 Astra |
| ALE-Bench | 1,564 | #7 / 56 | #13 / 82 | 2,951 GPT-6 Astra |
| WebDev Arena | 1,559 | #14 / 65 | #28 / 82 | 1,820 Claude Opus 5.5 |
| ARC-AGI | 92.5% | #14 / 46 (tied with 1) | #21 / 81 | 98.5% Claude Fable 5 |
| SimpleQA Verified | 53.0% | #13 / 53 | #22 / 81 | 76.0% Gemini 4 Argon |
| Chess puzzles | 52.0% | #7 / 53 | #15 / 80 | 76.0% GPT-6 Astra |
| Game puzzles | 36.0% | #9 / 49 | #19 / 77 | 84.0% GPT-6 Astra |
| ProofBench | 69.0% | #7 / 52 | #17 / 74 | 100.0% Claude Fable 5.1 |
| SimpleBench | 64.8% | #15 / 41 | #15 / 74 | 81.9% Claude Fable 5 |
| Frontiermath Tier 4 V2 | 56.1% | #9 / 44 | #17 / 67 | 100.0% GPT-6.1 Sol |
| FrontierMath | 47.2% | #5 / 33 | #5 / 65 | 51.7% GPT-5.5 |
| ForecastBench | 58.60 | #21 / 25 | #39 / 62 | 62.50 o3 |
| Vending Bench 2 | 5,787 | #16 / 44 | #22 / 57 | 15,515 GPT-6 Astra |
| Apex Agents | 48.9% | #16 / 35 | #28 / 50 | 82.4% Gemini 4 Argon |
| FrontierMath tier 4 | 31.3% | #3 / 33 | #3 / 48 | 39.6% GPT-5.5 Pro |
| FrontierCode | 46.5% | #5 / 29 | #14 / 43 | 54.6% Claude Opus 5.5 |
| Gdp Pdf | 24.0% | #5 / 24 (tied with 1) | #14 / 37 | 35.0% GPT-6.1 Sol |
| EnigmaEval | 23.5% | #6 / 17 | #6 / 36 | 39.3% Claude Fable 5 |
| Furniture Assembly | 42.5% | #5 / 20 (tied with 1) | #15 / 34 | 83.3% Claude Opus 5.5 |
| Blueprint Bench 2 | 14.5% | #16 / 22 | #25 / 31 | 54.4% Gemini 4 Argon |
| Gso | 47.1% | #3 / 16 | #5 / 28 | 88.2% Claude Fable 5.1 |
| Ebr Bench | 28.6% | #6 / 17 | #14 / 27 | 76.2% GPT-6 Astra |
| DeepSWE | 59.0% | #12 / 24 | #14 / 26 | 74.1% GPT-6 Astra |
| DeepResearch Bench | 50.2% | #6 / 15 | #6 / 24 | 55.3% Claude Opus 4.6 |
| Surface Evolver Bench | 87.5% | #5 / 20 | #5 / 24 | 95.0% Claude Fable 5 |
| Gbaeval | 70.9% | #3 / 22 | #3 / 22 | 79.6% Claude Opus 5 |
| Rli | 8.3% | #2 / 9 | #5 / 15 | 21.3% Claude Opus 5.5 |
| Posttrainbench | 33.8% | #4 / 11 | #4 / 11 | 41.8% Claude Fable 5 |
| Osworld 2 | 20.6% | #3 / 9 | #3 / 9 | 31.4% Claude Opus 5 |
| Btf3 | 14.0% | #5 / 7 | #6 / 8 | 14.9% GLM-5.3 |
For each test, the model's best effort level counts, as in the ranking. Source of the scores: Epoch AI, under CC BY 4.0.
What to compare Claude Opus 4.8 with
The models from other labs closest in capability and released in the same period, at most two per lab. Click any of them to see its page.
| Model | Lab | ECI | ELO | LiveBench | Release |
|---|---|---|---|---|---|
| GPT-5.4 Pro | OpenAI | 159.00 | n/a | n/a | Mar 5, 2026 |
| GPT-5.5 | OpenAI | 158.95 | 1,533 | 80.2 | Apr 23, 2026 |
| Claude Opus 4.8 | Anthropic | 158.26 | 1,507 | 76.2 | May 28, 2026 |
| Kimi K3 | Moonshot | 157.42 | 1,528 | 79.2 | Jul 16, 2026 |
| Gemini 3.7 Flash | Google DeepMind | 157.22 | 1,551 | 78.8 | Aug 13, 2026 |
| Gemini 3.8 Flash | Google DeepMind | 157.20 | 1,551 | 75.8 | Sep 2, 2026 |
| Qwen 3.8 Max | Alibaba | 156.88 | 1,536 | 78.5 | Aug 2, 2026 |
Claude Opus 4.8 or GPT-5.5?
GPT-5.5 is the model from another lab closest to Claude Opus 4.8 in capability. Across the 37 tests both took, this is the score:
| Test | Claude Opus 4.8 | GPT-5.5 |
|---|---|---|
| Blueprint Bench 2 | 14.5% | 36.2% |
| Osworld 2 | 20.6% | 13.0% |
| Game puzzles | 36.0% | 56.0% |
| ProofBench | 69.0% | 50.0% |
| Rli | 8.3% | 6.3% |
| Gbaeval | 70.9% | 53.2% |
| CritPt | 20.9% | 27.1% |
| Vending Bench 2 | 5,787 | 7,524 |
| Frontiermath Tier 4 V2 | 56.1% | 72.5% |
| Posttrainbench | 33.8% | 27.2% |
Unweighted score: each test counts one point, whether math or coding. The dot marks who did better on each row.
What Claude Opus 4.8 costs to deliver each task
Price per token is what is on the price sheet; cost per task is what lands on the invoice, because it depends on how many tokens the model spends. Each point is an effort level, published by whoever ran the test and compiled by Epoch AI. The further up and to the left, the more score per dollar.
ARC-AGI 2
The score scale does not start at zero.
ARC-AGI
The score scale does not start at zero.
DeepSWE
The score scale does not start at zero.
Other models from Anthropic
The models from the same lab closest in time, newest first.
| Model | Release | ECI | ELO | LiveBench | Access |
|---|---|---|---|---|---|
| Claude Opus 5.5 | Sep 22, 2026 | 166.82 | 1,584 | 83.2 | API access |
| Claude Fable 5.1 | Sep 1, 2026 | 164.65 | 1,586 | 83.4 | API access |
| Claude Opus 5 | Jul 24, 2026 | 162.60 | 1,573 | 80.1 | API access |
| Claude Sonnet 5 | Jun 30, 2026 | 156.36 | 1,491 | 76.0 | API access |
| Claude Fable 5 | Jun 9, 2026 | 162.13 | 1,542 | 83.0 | API access |
| Claude Opus 4.8 | May 28, 2026 | 158.26 | 1,507 | 76.2 | API access |
| Claude Opus 4.7 | Apr 16, 2026 | 156.32 | 1,532 | 76.5 | API access |
| Claude Sonnet 4.6 | Feb 17, 2026 | 152.39 | 1,504 | 73.0 | API access |
| Claude Opus 4.6 | Feb 5, 2026 | 155.27 | 1,550 | 74.5 | API access |
Have you used Claude Opus 4.8? Rate it
Users' opinion, not measurement: the rating is kept apart from the ranking and does not move anyone's position. One vote per browser, no sign-up, and you can change your rating later.
What people ask about Claude Opus 4.8
Does Claude Opus 4.8 still work?
Yes. It is a legacy model, but it is still available on the Anthropic API, Amazon Bedrock, Google Cloud, Microsoft Foundry and Claude Platform on AWS. Anthropic guarantees it will not be retired before May 28, 2027 on the platforms it operates, with at least 60 days' notice.
How much does Claude Opus 4.8 cost?
US$ 5 per million input tokens and US$ 25 per million output, the same as Opus 4.7. Cache reads cost US$ 0.50, cache writes US$ 6.25 (5 minutes) or US$ 10 (1 hour), and batch is US$ 2.50 and US$ 12.50. Fast mode, on the Anthropic API only, costs US$ 10 and US$ 50.
Why was a request to Fable or Opus 5.5 answered by Opus 4.8?
Because those models' safety classifiers blocked the request, usually a cybersecurity one, and the answer fell to the fallback model. In the Claude apps this happens by default, with a notice. On the API, only with the fallbacks parameter, and it is billed at Opus 4.8 rates.
Is it worth migrating from Opus 4.8 to Opus 5.5?
For most uses, yes: Opus 5.5 costs US$ 4 and US$ 20, rereads the cache for US$ 0.20 and is Anthropic's recommended starting point. Check three things first: thinking becomes always on, forced tool use stops working and Priority Tier does not exist on Opus 5.5.
Where does Claude Opus 4.8 rank among AI models?
In the ROO3 AI Benchmark, ordered by the Epoch AI ECI, Claude Opus 4.8 ranks #16 out of 267 models, with an ECI of 158.26. The ECI is a composite index that combines several hard benchmarks into a single scale. The position changes when a new model comes out, and the page is refreshed six times a day.
Is Claude Opus 4.8 better than GPT-5.5?
Across the 37 tests both models took and Epoch AI compiled, Claude Opus 4.8 comes out ahead on 9, behind on 28 and tied on 0. It is a test-by-test count with no weighting: a win in math counts the same as a win in coding. To choose between the two, look at the tests that resemble your own use.
What is Claude Opus 4.8 best at?
Against models of the same generation (released up to 9 months before and up to 3 months after it), the best relative results of Claude Opus 4.8 are: Lmca (#4 of 65); FrontierMath tier 4 (#3 of 33); WeirdML (#5 of 57). The yardstick is its position among the models of that period that took the same test.
Where do the numbers on this page come from?
From the same three sources as the ranking, all openly licensed: Epoch AI (ECI and individual tests, CC BY 4.0), Arena (human-preference ELO, CC BY 4.0) and LiveBench (overall average, CC BY-SA 4.0). ROO3 does not measure any model. When the page shows a figure published by the maker itself, it appears in the written analysis, labeled as the maker's, and never enters the ranking.
Where each number comes from
- Anthropic, Claude Opus 4.8 announcement
- Anthropic, Claude Opus 4.8 system card
- Anthropic, Claude Opus 4.8 overview (documentation)
- Anthropic, prompting Claude Opus 4.8 (documentation)
- Anthropic, pricing (documentation)
- Anthropic, model deprecations (documentation)
- Anthropic, migrating to Claude Opus 5.5 (documentation)
- Anthropic, refusals and fallback (documentation)
- Anthropic, platform release notes (documentation)
- Anthropic, Claude Opus 5 announcement (comparison with Opus 4.8)
- Anthropic, Claude Fable 5 announcement (fallback to Opus 4.8)
- Anthropic, Claude Opus 5.5 announcement (cybersecurity rerouting)
Epoch AI, "AI Benchmarking Hub". Published at epoch.ai. Data under the CC BY 4.0 licence, reordered by roo3.co.
The Arena (LMArena) leaderboard, from the public lmarena-ai/leaderboard-dataset on Hugging Face, under the CC BY 4.0 licence. We are not affiliated with the Arena.
LiveBench, by the LiveBench team, published at livebench.ai under the CC BY-SA 4.0 license. The overall average is recomputed by roo3.co with the same formula as the website (average of the categories), and those numbers stay under CC BY-SA 4.0. We are not affiliated with LiveBench.
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