Claude Sonnet 4.5 vs Kimi K2.6
At a Glance
| Compare | Claude Sonnet 4.5Anthropic |  Kimi K2.6Moonshot AI |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | #36 of 4627.7 score · 2/3 sources · provisional · missing LiveBench · full-core range 18.5–51.8 | #32 of 4650.5 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 33.6–67.0 |
| CostLower is better · Published-token output estimate | UnrankedNot in the 44-model eligible cohort | #21 of 44$0.095 per LiveBench case |
| EfficiencyHigher is better · MM Efficiency v1.5 | UnrankedNot in the 38-model eligible cohort | #24 of 3850.1 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 41.7–58.4 |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $3.00Anthropic ↗ · Sep 3, 2026 | $0.75Deepinfra ↗ · Sep 22, 2026 |
| Output priceFrom · USD / 1M tokens | $15.00Anthropic ↗ · Sep 3, 2026 | $3.50Deepinfra ↗ · Sep 22, 2026 |
| Context windowMaximum documented tokens | 200K | 262K |
| Model facts checked | Sep 3, 2026View model evidence → | Aug 28, 2026View model evidence → |
Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →
Available Benchmarks
| Benchmark | Claude Sonnet 4.5 | Kimi-K2.6 |
|---|---|---|
| LMArena Document Arenadocument-2026-09-13-d25aabda0010 · arena_rating · statistical tie | 1,449.81100% of row best · rating · claude-sonnet-4-5-20250929; 95% CI [1443.68972646, 1455.92640287]; votes 31455; rank 28 | 1,450.74100% of row best · rating · kimi-k2.6; 95% CI [1443.10467262, 1458.37474735]; votes 11291; rank 27 |
| LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader | 1,433.9499% of row best · rating · claude-sonnet-4-5-20250929-high-32k; 95% CI [1431.13982742, 1436.74901697]; votes 80980; rank 81 | 1,454.92100% of row best · rating · kimi-k2.6; 95% CI [1450.40277919, 1459.43693683]; votes 37502; rank 38 |
| ToneBench2026-09-11-10-task-4ef099199c9c · overall_score · unverified | 77.2594% of row best · points · Claude Sonnet 4.5 · 7,415 output tokens / case | 82.24100% of row best · points · Kimi K2.6 (thinking) · 18,080 output tokens / case |
| Overall ResultCounted from the protocol-matched rows above · 1 tie | 0 benchmark winsNo overall winner | 1 benchmark winNo overall winner |
Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.
Side-by-Side Facts
| Field | Claude Sonnet 4.5 | Kimi-K2.6 |
|---|---|---|
| Developer | Anthropic | Moonshot AI |
| Family | Claude 4 | Kimi K2 6 |
| Model | Claude Sonnet 4.5 | Kimi-K2.6 |
| Version | Claude Sonnet 4.5 | Kimi-K2.6 |
| Lifecycle | active | active |
| Released | 2025-09-29 | 2026-04-20 |
| Knowledge cutoff | 2025-01-01 | Unknown |
| Input modalities | Text, Image | Text, Image |
| Output modalities | Text | Text |
| Context window | 200K | 262K |
| Total parameters | Unknown | 1T |
| Active parameters | Unknown | 32B |
| License | Unknown | other |
| Open weights | No | Yes |
| API available | Yes | Yes |
| Self-hostable | No | Yes |
| Provider access | Anthropic (Standard) | Deepinfra (Standard), Fireworks Ai (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard) |
| Capabilities | chat, generation, reasoning, structured_outputs, tools | chat, generation, reasoning, tools |
Claude Sonnet 4.5 Capabilities
Kimi K2.6 Capabilities
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Claude Sonnet 4.5Anthropic | vs |  GLM-5.3Z.ai | cross-developer peerstext |
Claude Sonnet 4.5Anthropic | vs |  Hy4 previewTencent | cross-developer peerstext |
Claude Sonnet 4.5Anthropic | vs | Seed 2.1 ProByteDance Seed | cross-developer peersimage, text |
Claude Sonnet 4.5Anthropic | vs |  Mistral Large 3Mistral AI | cross-developer peersimage, text |
Primary Evidence
Sources and Freshness
Questions
Claude Sonnet 4.5 vs Kimi K2.6 FAQs
Is Claude Sonnet 4.5 or Kimi K2.6 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Claude Sonnet 4.5 and Kimi K2.6, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Claude Sonnet 4.5 or Kimi K2.6?+
Claude Sonnet 4.5 is $3.00 and Kimi K2.6 is $0.75 per million tokens, so Kimi K2.6 is cheaper on this metric. Claude Sonnet 4.5 is $15.00 and Kimi K2.6 is $3.50 per million tokens, so Kimi K2.6 is cheaper on this metric.
Which has a larger context window, Claude Sonnet 4.5 or Kimi K2.6?+
Kimi K2.6 has the larger sourced context window. Claude Sonnet 4.5 supports 200K and Kimi K2.6 supports 262K.
Which performs better in benchmarks, Claude Sonnet 4.5 or Kimi K2.6?+
There is no overall benchmark winner: An overall winner requires at least two decisive benchmarks from at least two original publishers.
Can Claude Sonnet 4.5 or Kimi K2.6 be self-hosted?+
Kimi K2.6 is the only model in this pair currently marked as self-hostable. Claude Sonnet 4.5 is not marked open weight; Kimi K2.6 is open weight.
Can Claude Sonnet 4.5 and Kimi K2.6 understand images?+
Claude Sonnet 4.5 is documented with image input; Kimi K2.6 is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Claude Sonnet 4.5 or Kimi K2.6?+
Neither has a larger sourced maximum output. Claude Sonnet 4.5 is 64K and Kimi K2.6 is —.
Do Claude Sonnet 4.5 and Kimi K2.6 support reasoning and tool use?+
Claude Sonnet 4.5: reasoning, tool calling, and image input. Kimi K2.6: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Claude Sonnet 4.5 or Kimi K2.6?+
Claude Sonnet 4.5 has 1 sourced provider route; Kimi K2.6 has 5, so Kimi K2.6 has broader tracked availability.
Which offers better value, Claude Sonnet 4.5 or Kimi K2.6?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.