Moonshot AI, released Apr 21, 2026
Kimi K2.6price, context, benchmarks and release details
- Input, per 1M tokens
- $0.95models.devFirst-party hosted API; MIT models.dev transcription. Provider documentation: https://platform.moonshot.ai/docs/api/chat. Exact canonical endpoint; lowest short-context Standard USD token tier; cache/batch discounts excluded. Deprecated endpoints excluded; moonshotai/kimi-k2.6
Retrieved Oct 9, 2026 · MIT
Open source ↗ - Output, per 1M tokens
- $4.00models.devFirst-party hosted API; MIT models.dev transcription. Provider documentation: https://platform.moonshot.ai/docs/api/chat. Exact canonical endpoint; lowest short-context Standard USD token tier; cache/batch discounts excluded. Deprecated endpoints excluded; moonshotai/kimi-k2.6
Retrieved Oct 9, 2026 · MIT
Open source ↗ - Context window
- 262Kmodels.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗ - Max output
- 262Kmodels.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗ - Released
- Apr 21, 2026models.devPublished source fact
Retrieved Oct 9, 2026 · MIT
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, 06:15 UTC.
Around it on the leaderboard
- 36 Grok 4.7 65.5
- 37 Grok 4.5 64.8
- 38 Kimi K2.6 64.0
- 39 Qwen3.5 397B-A17B 64.0
- 40 GPT-5.5 Pro 63.5
Benchmark results
22 benchmarks, 23 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 ↗ 90.8
Open source ↗ 89.3
Open source ↗ 51.3
Open source ↗ 70.0
Open source ↗ 94.0
Open source ↗ 75.0
Open source ↗ 78.5
Open source ↗ 25.6
Open source ↗ 57.2
Open source ↗ 97.0
Open source ↗ 96.1
Open source ↗ 54.0
Open source ↗ 90.0
Open source ↗ 61.4
Open source ↗ 96.1
Open source ↗ 78.3
Open source ↗ 78.9
Open source ↗ 59.1
Open source ↗ 55.0
Open source ↗ 26.7
SWE-bench Verifiedcoding 80.2%Official model cards via models.devLab-reported; metric resolved; transcribed by MIT models.dev catalog; not independently evaluated [variant]
Retrieved Oct 9, 2026 · factual citation; MIT transcription
Open source ↗
80.2 2 settings
- Setting 1 76.7%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published May 8, 2026
Retrieved Oct 9, 2026 · CC-BY
Open source ↗ - Setting 2 80.2%Official model cards via models.devLab-reported; metric resolved; transcribed by MIT models.dev catalog; not independently evaluated [variant]
Retrieved Oct 9, 2026 · factual citation; MIT transcription
Open source ↗
Open source ↗ 78.2
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
- YesHugging Face HubPublic Hub repo with weight files; gating/repo upload date is not release date
Retrieved Oct 9, 2026 · factual metadata; model-specific licenses
Open source ↗ - License
- otherHugging Face HubPublished source fact
Retrieved Oct 9, 2026 · factual metadata; model-specific licenses
Open source ↗ - Input modalities
- text, image, videomodels.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗ - First seen by SuperIndex
- Oct 8, 2026
- Coverage
- 68% of expected source weight
Reported (4)
- Epoch AI BenchmarkingOct 8, 2026
- Official model cards via models.devOct 8, 2026
- LiveBenchOct 8, 2026
- LMArena / ArenaOct 8, 2026
Awaiting (3)
- ARC Prize13% of weight
- Humanity’s Last Exam13% 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.