Anthropic, released Oct 15, 2025
Claude Haiku 4.5price, context, benchmarks and release details
Provisional: not enough results to rank yet 64% confidence 64 percent, Medium confidence, 2 of 7 expected sources in
60.5
SI Score
#62 of 142 ranked models
- Input, per 1M tokens
- $1.00models.devFirst-party hosted API; MIT models.dev transcription. Provider documentation: https://docs.anthropic.com/en/docs/about-claude/models. Exact canonical endpoint; lowest short-context Standard USD token tier; cache/batch discounts excluded. Deprecated endpoints excluded; anthropic/claude-haiku-4-5-20251001
Retrieved Oct 9, 2026 · MIT
Open source ↗ - Output, per 1M tokens
- $5.00models.devFirst-party hosted API; MIT models.dev transcription. Provider documentation: https://docs.anthropic.com/en/docs/about-claude/models. Exact canonical endpoint; lowest short-context Standard USD token tier; cache/batch discounts excluded. Deprecated endpoints excluded; anthropic/claude-haiku-4-5-20251001
Retrieved Oct 9, 2026 · MIT
Open source ↗ - Context window
- 200Kmodels.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗ - Max output
- 64Kmodels.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗ - Released
- Oct 15, 2025models.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗
How the score breaks down
Coding (weight 40 percent) —
Math (weight 15 percent) 78.2
Preference (weight 15 percent) 72.7
Reasoning (weight 30 percent) 65.8
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, 06:15 UTC.
Around it on the leaderboard
- 60 DeepSeek V4 Flash 0731 61.0
- 61 Hy3 60.7
- 62 Claude Haiku 4.5 60.5
- 63 Qwen3.5 Flash 59.5
- 64 Claude Haiku 5.5 59.4
Benchmark results
4 benchmarks, 7 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.
GPQA Diamondreasoning 71.2%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] 32KPublished Oct 22, 2025
Retrieved Oct 9, 2026 · CC-BY
Open source ↗
71.2 2 settings
- 32K thinking 71.2%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] 32KPublished Oct 22, 2025
Retrieved Oct 9, 2026 · CC-BY
Open source ↗ - Setting 2 60.5%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published Oct 16, 2025
Retrieved Oct 9, 2026 · CC-BY
Open source ↗
MATH Level 5math 96.4%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] 32KPublished Oct 22, 2025
Retrieved Oct 9, 2026 · CC-BY
Open source ↗
96.4 2 settings
- 32K thinking 96.4%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] 32KPublished Oct 22, 2025
Retrieved Oct 9, 2026 · CC-BY
Open source ↗ - Setting 2 86.9%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published Oct 16, 2025
Retrieved Oct 9, 2026 · CC-BY
Open source ↗
OTIS Mock AIME 2024–2025math 66.7%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] 32KPublished Oct 22, 2025
Retrieved Oct 9, 2026 · CC-BY
Open source ↗
66.7 2 settings
- 32K thinking 66.7%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] 32KPublished Oct 22, 2025
Retrieved Oct 9, 2026 · CC-BY
Open source ↗ - Setting 2 35.8%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published Oct 16, 2025
Retrieved Oct 9, 2026 · CC-BY
Open source ↗
LMArena Textpreference 1396.4 eloLMArena / ArenaPublished source fact [variant] text / overallPublished Oct 8, 2026
Retrieved Oct 9, 2026 · CC-BY-4.0
Open source ↗ 72.7
Open source ↗ 72.7
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
- 51% of expected source weight
Reported (2)
- Epoch AI BenchmarkingOct 8, 2026
- LMArena / ArenaOct 8, 2026
Awaiting (5)
- ARC Prize13% of weight
- Humanity’s Last Exam13% of weight
- Official model cards via models.dev4% of weight
- LiveBench13% of weight
- Terminal-Bench6% of weight
Confidence rises as pending sources publish. Some sources never cover some models, so confidence reaches 100% at 80% of expected weight.