Models / Anthropic/ Claude Opus 4.8 (Fast)

Claude Opus 4.8 (Fast)

Anthropic · released May 27, 2026

Input: text, images and documents. Output: text.InputOutput
Type
Closed
Input
$10.00
Output
$50.00
Cached
$1.00

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

Our take

Written Sep 1, 2026

Claude Opus 4.8 (Fast) is Anthropic's premium reasoning model with a one-million-token request limit and a fast-throughput variant. It handles text, images and files, but carries a steep per-token cost and no measured quality scores in our data.

Who should pick it

Choose this for long-document analysis at one million tokens of context, or premium reasoning where latency matters and the direct API throughput suffices. Use it for multimodal prompts mixing documents, images and text. Skip it if cost is a constraint, if you need verified quality benchmarks, or if you rely on the second provider whose throughput is undisclosed.

The case for it

  • One-million-token request limit — ten times the threshold that defines most current long-context models.
  • Fast variant delivers 153 tokens per second via Anthropic's own endpoint.

The case against it

  • Very high per-token cost, with output priced steeply even at the input tier.
  • No benchmark scores, Elo, or task scores in our data — quality is unverified.
  • Throughput undisclosed on one of two providers.
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How good is it?

We hold no score for this model.

So there is no figure here for everyday use, coding, agent work or writing. That is a gap in our data, not a low score.

Where these scores come from →

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Where to rent it

Prices checked 31 days ago — each listing carries its own date.

Cheapest published offer

Anthropic, through OpenRouter

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
$10.00 in / $50.00 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
OpenRouterOpenRouter's own listing$10.00 / $50.00checked 31 days ago1Mnot measuredUnknownUnknownUnknown
AnthropicThrough OpenRouter$10.00 / $50.00checked 31 days ago1Mnot measuredNoYes30 daysUnknown

Across the 2 listings we hold: 1 says it does not train on prompts, 0 say they do and 1 does not say. 0 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
OpenRouterOpenRouter's own listing✓✓✓
AnthropicThrough OpenRouter✓✓✓

Tool calling: 2 of 2 listings say yes. JSON output: 2 of 2 listings say yes. Strict schema: 2 of 2 listings say yes.

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Models people weigh against Claude Opus 4.8 (Fast)

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When we formed this view

Recent changes

Jul 26, 2026ListedListed on LLMap
What movedfirst indexed by our pipeline
May 27, 2026AnnouncedClaude Opus 4.8 (Fast) announced by Anthropic

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

  • No independent board has scored it, so we hold no quality figures at all.
  • Nothing we hold says whether an endpoint streams, so we do not show it either way.
  • 1 of 2 listings does not say whether it trains on prompts.
  • We hold no batch or off-peak rate for any of its listings.
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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

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-4-8-fast

Machine-readable model card (omc.json) →

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