Anthropic, released Mar 13, 2024

Claude Haiku 3price, context, benchmarks and release details

Provisional: not enough results to rank yet 93% confidence 93 percent, High confidence, 2 of 4 expected sources in
39.9
SI Score
#126 of 142 ranked models
Input, per 1M tokens
not yet reported
Output, per 1M tokens
not yet reported
Context window
200Kmodels.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗
Max output
4.1Kmodels.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗
Released
Mar 13, 2024models.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗

How the score breaks down

Coding (weight 40 percent) —
Math (weight 15 percent) 10.5
Preference (weight 15 percent) 49.3
Reasoning (weight 30 percent) 36.3

Weights: reasoning 30%, math 15%, coding 40%, preference 15%. Results use fixed 0–100 scales before averaging, and thin evidence is pulled toward 50. Method si-v3-retained-evidence-2, computed Oct 9, 2026, 05:13 UTC.

Around it on the leaderboard

  1. 124 GPT-4.1 41.5
  2. 125 Claude Haiku 3.5 40.8
  3. 126 Claude Haiku 3 39.9
  4. 127 Qwen2.5-Coder-32B-Instruct 39.6
  5. 128 Gemma 3 4B IT 39.2

Full leaderboard

Benchmark results

4 benchmarks, 4 results

Each row shows the best published result. Where a model was tested at several settings, such as reasoning effort, open the row to see each one. Hover or tap a value for its source.

GPQA Diamondreasoning 36.3%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published Jan 27, 2025 Retrieved Oct 9, 2026 · CC-BY
Open source ↗
36.3
MATH Level 5math 14.9%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published Jan 27, 2025 Retrieved Oct 9, 2026 · CC-BY
Open source ↗
14.9
OTIS Mock AIME 2024–2025math 1.8%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published Feb 25, 2025 Retrieved Oct 9, 2026 · CC-BY
Open source ↗
1.8
LMArena Textpreference 1194.7 eloLMArena / ArenaPublished source fact [variant] text / overallPublished Oct 8, 2026 Retrieved Oct 9, 2026 · CC-BY-4.0
Open source ↗
49.3

Normalization uses a fixed 0–100 scale for each unit, independent of other models. Compare evaluation conditions before reading a small gap as decisive. “Lab-reported” marks the provider's own published figure.

Details and sources

Open weights
Nomodels.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗
License
not yet reported
Input modalities
text, image, pdfmodels.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗
First seen by SuperIndex
Oct 8, 2026
Coverage
75% of expected source weight

Reported (2)

  • Epoch AI BenchmarkingOct 8, 2026
  • LMArena / ArenaOct 8, 2026

Awaiting (2)

  • Official model cards via models.dev7% of weight
  • LiveBench19% of weight

Confidence rises as pending sources publish. Some sources never cover some models, so confidence reaches 100% at 80% of expected weight.

What changed

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