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Anthropic: Claude Opus 4.8 (Fast)
Anthropic
•
Claude Opus 4.8 (Max)
•
Released 
May 2026

Anthropic
Claude Opus 4.8 (Max)

Anthropic's flagship Opus at up to 2.5x output speed for latency-sensitive long-horizon coding and agent workflows.

Modality:
Text
Image
PDF
model ID
anthropic/claude-opus-4.8-fast
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Output Speed *

0.00
tok/s

Intelligence Index *

41.8
/ 100

Context Window *

1000000
tokens

Input price

60
Anytoken

Output price

300
Anytoken
Claude Opus 4.8 Fast Mode: Full Opus Quality at 2.5x Output Speed Claude Opus 4.8 (Fast) is Anthropic's Opus 4.8 model served in fast mode, a research-preview serving configuration on the Claude API. It is the same weights and reasoning as standard Opus 4.8, Anthropic's flagship Opus-tier model for complex agentic coding and enterprise work, but delivered at up to 2.5x higher output tokens per second at premium pricing. Quality and capabilities are identical; only throughput and cost change. It suits latency-sensitive workloads—live debugging, interactive agents, and long code generation—where streaming speed materially improves the developer or end-user experience. Start building with Claude Opus 4.8 via the AnyAPI.ai API.

Performance

Where Fast Mode Actually Helps: Long Output Streaming

Fast mode's advantage is concentrated in throughput, not intelligence. It delivers up to 2.5x higher output tokens per second from Claude Opus 4.8 at premium pricing. Crucially, it does not speed up time to first token, the pause before the first word appears. That means short prompts feel unchanged, while long code generations and multi-step agent transcripts stream back noticeably faster. Because the underlying model is identical, coding and agentic quality match standard Opus 4.8—SWE-Bench Pro of 69.2% per Anthropic's reporting. In production, this makes fast mode a per-session decision for interactive, output-heavy work rather than a default.

Benchmarks

Fast Mode Inherits Standard Opus 4.8 Coding Scores

Because fast mode runs identical weights, all published Opus 4.8 benchmarks apply. On coding, <cite index="19-8">Anthropic reports SWE-Bench Pro of 69.2% for Opus 4.8 versus 64.3% for Opus 4.7 and 58.6% for GPT-5.5.</cite> Independent testing notes vendor-harness numbers should be read as generation-over-generation signals: <cite index="20-19,20-20">absolute numbers should not be compared side by side; Anthropic's 69.2% means the model solved roughly seven out of ten problems with an agent that could explore and test.</cite> On agentic work, <cite index="21-11">Anthropic states Opus 4.8 is the only model to complete every case end-to-end on its Super-Agent benchmark.</cite> These reflect capability, not fast mode's speed gain.

Output Speed

*
0.00
tok/s

Intelligence Index

*
41.8
/ 100

MMLU *

Broad world knowledge and problem-solving
0
%

GPQA *

PhD-level scientific reasoning across physics, biology, chemistry.
92
%

HLE *

Adherence to multi-step structured instructions.
49
%

LiveCodeBench *

Tool-calling reliability in long agentic loops.
0
%

Technical Specifications

What the model supports

Fast mode is a serving option, not a separate model. <cite index="31-7,31-8,31-9">It is not a different model; it uses Claude Opus with a different API configuration, and you get identical quality and capabilities with faster responses.</cite> Opus 4.8 itself accepts text and image input with text output, and <cite index="26-7">supports the 1M token context window by default, 128k max output tokens, adaptive thinking, and the same tools as Opus 4.7.</cite> The critical operational detail: fast mode raises output tokens per second, not time to first token, so its value depends entirely on generating long outputs.
Verified Specifications — 
Claude Opus 4.8 (Max)
*
Input modalities
Text
Image
PDF
output modalities
Text
Context window
1000000
 tokens
Maximum output tokens
128000
Reasoning
Yes
Knowledge cutoff
May 2026
Pricing (standard)
60
 AnyTokens in
 / 
300
 AnyTokens out

Limitations & Trade-offs

Where Claude Opus 4.8 (Max) falls short

1
Research preview, restricted availability. Fast mode is not generally available. <cite index="27-5,27-6,27-9,27-10">It is in research preview requiring account-manager access, is available on the Claude API and Claude Managed Agents only, and is not available on Amazon Bedrock, Google Cloud, or Microsoft Foundry.</cite> Feature, pricing, and availability may change. Teams needing stable, multi-cloud deployment should plan around standard Opus 4.8, which carries no such preview restriction.
2
No time-to-first-token improvement. Fast mode raises only output tokens per second. <cite index="34-14,34-15">The metric that improves is OTPS, up to 2.5x standard speed; however, TTFT is not affected by fast mode.</cite> Short prompts and low-output requests therefore see little benefit while still paying the premium. Workloads dominated by request setup latency rather than long generation gain nothing from this configuration.
3
Premium pricing on an already expensive tier. Opus 4.8 is a flagship-priced model, and fast mode roughly doubles per-token cost. This makes it the most expensive way to run an already premium model, so it is poorly suited to high-volume or cost-sensitive generation. For those workloads, standard Opus 4.8, a Sonnet-class model, or lower effort levels are more economical.
4
Shared, throttled rate-limit pool. <cite index="34-8,34-9">Fast mode has dedicated rate limits separate from standard Opus, shared across Opus 4.8, 4.7, and 4.6; when the limit is exceeded, fast mode automatically falls back to standard speed.</cite> Under sustained load, effective throughput may drop back to standard rates, so capacity planning cannot assume 2.5x is always available for large parallel agent fleets.

Best-Fit Workloads

Where this model earns its place

01

Interactive coding and live debugging

‍
Fast mode's throughput gain is most valuable when an engineer is watching output stream. Toggle it on with /fast when you need speed for interactive work like rapid iteration or live debugging, and off when cost matters more than latency. Long code edits arrive faster, keeping developers in flow. Since quality equals standard Opus 4.8's strong coding scores, there is no capability trade-off—only cost.

02

Latency-sensitive agent UIs

‍
For user-facing agents that generate long transcripts or multi-step plans, faster streaming reduces perceived wait. Because tool calling is meaningfully more efficient, using fewer steps for the same intelligence, combining Opus 4.8's agentic efficiency with fast serving improves responsiveness in interactive deployments. Note the unchanged TTFT means the first token still arrives at standard latency.

03

Long-form generation with a human in the loop

‍
Drafting long documents, detailed analyses, or large refactors where someone reviews output as it streams benefits directly from higher output tokens per second. The advantage scales with output length, so short answers gain little. Treat fast mode as a per-session choice enabled when long generation is expected, then disabled to control spend.

04

Rapid prototyping of agentic pipelines

‍
During development of long-horizon agent workflows, faster iteration shortens the feedback loop when engineers actively observe runs. Fast mode's identical behavior to standard Opus 4.8 means prototypes translate cleanly to production on standard serving. Because it is a research preview with shared rate limits, avoid depending on 2.5x throughput for scaled, unattended production runs.

Pricing in anytokens via AnyAPI
Input
60
₳
Output
300
₳
Cache write
75
₳
Cache read
6
₳
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PerformanceBenchmarksTechnical SpecificationsLimitations & Trade-offsBest-Fit WorkloadsIntegrationFAQ

Integration

Access Claude Opus 4.8 (Max) via AnyAPI.ai

Access Claude Opus 4.8 (Max) through AnyAPI.ai using a unified API built for multi-model AI applications. Integrate Claude Opus 4.8 (Max) without maintaining a separate provider-specific connection, and keep the flexibility to test, switch, or combine models as your application requirements evolve.

01

One API integration

Access Claude Opus 4.8 (Max) and other AI models through the same API workflow instead of maintaining separate integrations for every provider.

02

Easy model switching

Test Claude Opus 4.8 (Max) against alternative models or switch models as your performance, capability, or cost requirements change without rebuilding your application around another provider API.

03

Flexible for production

Use Claude Opus 4.8 (Max) from experimentation through production while keeping your AI stack flexible as workloads, traffic, and model requirements evolve.

04

Multi-model applications

Use Claude Opus 4.8 (Max) for the workloads where it performs best and combine it with other models for tasks that require different capabilities, performance, or efficiency.

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Frequently Asked Questions

Answers to common questions about integrating and using this AI model via AnyAPI.ai

No. Fast mode is a serving configuration, not a separate model. It runs the exact same Opus 4.8 weights and reasoning, delivering up to 2.5x higher output tokens per second at premium pricing. Intelligence, capabilities, and benchmark performance are identical to standard Opus 4.8—only throughput and cost differ.

Only partly. Fast mode increases output tokens per second, so long responses finish faster. It does not improve time to first token—the initial pause before the first word appears is unchanged. Short prompts feel similar, while long code generation or agent transcripts stream back noticeably quicker.

On the Claude API, send the fast-mode-2026-02-01 beta header and set speed to "fast" on your Messages request against claude-opus-4-8. Fast mode is a research preview available on the Claude API and Claude Managed Agents only, and typically requires account-manager access or a waitlist.

Claude Opus 4.8 supports a 1,000,000-token context window by default on the Claude API and 128,000 max output tokens. Batch processing can extend output to 300,000 tokens using a beta header. Fast mode does not change these limits, since it uses the same underlying model.

It depends on the workload. Fast mode roughly doubles per-token cost and helps only when generating long outputs someone is actively watching—interactive coding, live debugging, or latency-sensitive agents. For unattended pipelines, batch jobs, or short responses, standard Opus 4.8 is the more economical choice.

* Benchmark data source: Artificial Analysis artificialanalysis.ai