Claude Opus 4.6$11.000/MClaude Opus 4.5$33.000/MClaude Sonnet 3.7$6.600/MClaude Opus 3$33.000/MClaude 2.1$12.800/MClaude 2$12.800/MGPT-5$3.875/MGPT-4.5$97.500/MGPT-4 Turbo Preview$16.000/MGPT-4$39.000/MGPT-4-32k$78.000/Mo3$19.000/Mo3-mini$2.090/Mo4-mini$2.090/Mo1$28.500/Mo1-mini$5.700/Mo1-preview$28.500/MGemini 2.5 Pro$3.875/MGemini 1.5 Pro$2.375/MGemini 1.0 Ultra$12.000/MGemini 1.0 Pro$0.800/MPaLM 2 Bison$0.500/MPaLM 2 Unicorn$5.000/MGemma 3 27B$0.270/MGrok 3$6.600/MGrok 2$4.400/MGrok 1.5$8.000/MDeepSeek-V3$0.519/MDeepSeek-V3-0324$0.519/MDeepSeek-R1$1.042/MClaude Opus 4.6$11.000/MClaude Opus 4.5$33.000/MClaude Sonnet 3.7$6.600/MClaude Opus 3$33.000/MClaude 2.1$12.800/MClaude 2$12.800/MGPT-5$3.875/MGPT-4.5$97.500/MGPT-4 Turbo Preview$16.000/MGPT-4$39.000/MGPT-4-32k$78.000/Mo3$19.000/Mo3-mini$2.090/Mo4-mini$2.090/Mo1$28.500/Mo1-mini$5.700/Mo1-preview$28.500/MGemini 2.5 Pro$3.875/MGemini 1.5 Pro$2.375/MGemini 1.0 Ultra$12.000/MGemini 1.0 Pro$0.800/MPaLM 2 Bison$0.500/MPaLM 2 Unicorn$5.000/MGemma 3 27B$0.270/MGrok 3$6.600/MGrok 2$4.400/MGrok 1.5$8.000/MDeepSeek-V3$0.519/MDeepSeek-V3-0324$0.519/MDeepSeek-R1$1.042/M
BETA
Anthropic
Anthropic
MultimodalLIVE INDEX

Claude Opus 4.6 (Fast)

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The flagship of the Claude 4 generation. 1M-token context is GA, and Opus 4.6 leads on agentic coding, long-horizon reasoning and tool-use reliability.

Profile inherited from upstream Claude Opus 4.6 — this is a hosted variant of the same open-weights model.

INPUT
$30.000/M
per million input tokens
OUTPUT
$150.000/M
per million output tokens
BLENDED 70/30
$66.000/M
default reference rate
CONTEXT
1.0M
1,000,000 tokens
What it's good at
  • Agentic coding (Claude Code)
  • 1M-token context, GA
  • Tool use & function calling
  • Multi-step reasoning
  • Faithful to long instructions
Typical use cases
  • Engineering copilots
  • Codebase-wide refactors
  • Long-document Q&A
  • Multi-step agent workflows
Benchmarks
vs. best public score
Scores inherited from Claude Opus 4.6 — this is a hosted variant of the same open-weights model, so the underlying benchmark scores are identical.
MMLU88%
Multitask academic knowledge across 57 subjects.
GPQA Diamond79%
Graduate-level science questions, "Google-proof".
MATH92%
High-school competition math problems.
HumanEval95%
Python function synthesis from docstrings.
SWE-bench Verified72%
Real GitHub issues solved end-to-end.
LMArena Elo1378 Elo
Crowd-sourced head-to-head preference Elo rating.
Hand-curated from each provider's published reports and public leaderboards. Methodology varies across sources — treat as directional rather than authoritative.
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