Anthropic, released Oct 7, 2026
Claude Haiku 5.5price, context, benchmarks and release details
- Input, per 1M tokens
- $0.10Anthropic models & pricingOfficial Claude API; lowest short-context on-demand tier; batch/cache/long-context rates excluded
Retrieved Oct 9, 2026 · factual citation
Open source ↗ - Output, per 1M tokens
- $0.50Anthropic models & pricingOfficial Claude API; lowest short-context on-demand tier; batch/cache/long-context rates excluded
Retrieved Oct 9, 2026 · factual citation
Open source ↗ - Context window
- 1MAnthropic models & pricingOfficial Claude API; lowest short-context on-demand tier; batch/cache/long-context rates excluded
Retrieved Oct 9, 2026 · factual citation
Open source ↗ - Max output
- 128KAnthropic models & pricingOfficial Claude API; lowest short-context on-demand tier; batch/cache/long-context rates excluded
Retrieved Oct 9, 2026 · factual citation
Open source ↗ - Released
- Oct 7, 2026Anthropic models & pricingOfficial Claude API; lowest short-context on-demand tier; batch/cache/long-context rates excluded
Retrieved Oct 9, 2026 · factual citation
Open source ↗
How the score breaks down
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
- 62 Claude Haiku 4.5 60.5
- 63 Qwen3.5 Flash 59.5
- 64 Claude Haiku 5.5 59.4
- 65 GLM-5 59.4
- 66 Kimi K2.5 59.0
Benchmark results
20 benchmarks, 20 resultsEach 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.
Open source ↗ 45.9
Open source ↗ 30.1
Open source ↗ 57.4
Open source ↗ 96.0
Open source ↗ 10.6
Open source ↗ 66.0
Open source ↗ 92.0
Open source ↗ 86.5
Open source ↗ 94.0
Open source ↗ 97.0
Open source ↗ 98.0
Open source ↗ 67.0
Open source ↗ 83.7
Open source ↗ 50.3
Open source ↗ 78.3
Open source ↗ 77.5
Open source ↗ 68.2
Open source ↗ 60.0
Open source ↗ 43.3
Open source ↗ 39.2
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
- 54% of expected source weight
Reported (3)
- Humanity’s Last ExamOct 8, 2026
- Official model cards via models.devOct 8, 2026
- LiveBenchOct 8, 2026
Awaiting (1)
- LMArena / Arena46% of weight
Confidence rises as pending sources publish. Some sources never cover some models, so confidence reaches 100% at 80% of expected weight.