Claude Opus 4.8

AnthropicProprietary

Anthropic's workhorse frontier model — slightly below Fable 5, meaningfully cheaper, same graceful effort curve.

Index @ High

79.6

Context

$/M in · out

$5 · $25

Median speed

55 tok/s

Released

Feb 10, 2026

02·Which effort for which task

The sweet spot, per task

Cheapest effort tier that keeps ≥96% of this model's peak quality on the benchmarks behind each task type. Below the floor number, quality is not okay — it just fails quietly.

Everyday writing & Q&A

Low

Chat, drafting, summaries, general questions.

keeps 96.5% of peak−95% cost

Code assist

Medium

Autocomplete, single functions, small fixes.

keeps 96.6% of peak−88% cost

Coding agents

High

Real repos, multi-file changes, end-to-end tickets.

keeps 98.0% of peak−64% cost

Math & quantitative

High

Derivations, statistics, financial models.

keeps 96.7% of peak−64% cost

⚠ at Low: only 76% of peak — avoid

Hard research problems

High

Novel, frontier, genuinely difficult questions.

keeps 97.5% of peak−64% cost

Agents & tool use

High

Long workflows with tools, policies, and state.

keeps 98.7% of peak−64% cost

03·The effort ladder

Quality and cost, tier by tier

On everyday tasks, Low keeps 96.5% of X-High quality at $0.037 vs $0.72 per task.

Intelligence Index by effort

Cost per typical task by effort

04·Benchmark detail

Scores at Medium

Low Medium High X-High

at Mediumat X-High (peak)

Benchmark	Medium	Peak	What it predicts
MMLU-Pro	86.7	88.0	Everyday Q&A · Drafting emails & docs · Summarizing articles
GPQA Diamond	81.0	88.0	Technical analysis · Root-cause debugging · Scientific writing
Humanity's Last Exam	27.6	30.0	Novel research questions · Frontier problem solving
AIME 2025	80.0	93.0	Financial modeling · Statistics · Algorithm design
SWE-bench Verified	75.2	80.0	Coding agents · Bug fixing in real repos · Multi-file refactors
LiveCodeBench	78.0	83.0	Writing functions from scratch · Algorithms · Code autocomplete
τ²-bench	79.1	86.0	Tool-using agents · Customer-facing automation · Multi-step workflows
IFEval	92.1	93.0	Structured output (JSON) · Templated generation · Batch pipelines

06·Drift

Is it still the same model this week?

Weekly Intelligence Index · dashed rules mark serving-change events

No serving-change events detected for Claude Opus 4.8 in the tracked window.

07·Call it

One key, this model, your effort

The gateway speaks the OpenAI Chat Completions dialect. Pick a host with claude-opus-4.8@host syntax, set reasoning_effort, and the sweet spot above becomes one line of config. Full docs →

chat with Claude Opus 4.8

curl https://models.fyi/api/v1/chat/completions \
  -H "Authorization: Bearer $MFYI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "claude-opus-4.8",
    "reasoning_effort": "low",
    "messages": [{"role": "user", "content": "Hello"}]
  }'
# local dev: replace https://models.fyi with http://localhost:3000