DeepSeek R1 vs Kimi K2 Thinking
At a Glance
| Compare |  DeepSeek R1DeepSeek |  Kimi K2 ThinkingMoonshot AI |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v4.4 | #42 of 570.4 score · 1/3 sources · single-source provisional · missing LiveBench, ARC-AGI-2 · full-core range 0.1–66.8 | UnrankedNot in the 57-model eligible cohort |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.70Openrouter ↗ · Aug 28, 2026 | $0.60Openrouter ↗ · Oct 19, 2026 |
| Output priceFrom · USD / 1M tokens | $2.50Openrouter ↗ · Aug 28, 2026 | $2.50Openrouter ↗ · Oct 19, 2026 |
| Context windowMaximum documented tokens | 164K | 262K |
| Model facts checked | Aug 28, 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
Side-by-Side Facts
| Field | DeepSeek-R1 | Kimi-K2-Thinking |
|---|---|---|
| Developer | DeepSeek | Moonshot AI |
| Family | Deepseek R1 | Kimi K2 Thinking |
| Model | DeepSeek-R1 | Kimi-K2-Thinking |
| Version | DeepSeek-R1 | Kimi-K2-Thinking |
| Lifecycle | active | active |
| Released | 2025-01-20 | 2025-11-06 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text | Text |
| Output modalities | Text | Text |
| Context window | 164K | 262K |
| Total parameters | 684.5B | 1.03T |
| Active parameters | 37B | 32B |
| License | mit | other |
| Open weights | Yes | Yes |
| API available | Yes | Yes |
| Self-hostable | Yes | Yes |
| Provider access | Hugging Face (Standard), Openrouter (Standard) | Hugging Face (Standard), Openrouter (Standard) |
| Capabilities | chat, generation, reasoning | chat, generation, reasoning, tools |
DeepSeek R1 Capabilities
Kimi K2 Thinking Capabilities
Related Comparisons
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|---|---|---|---|
DeepSeek-R1DeepSeek | vs | cross-developer peerstext | |
DeepSeek-R1DeepSeek | vs |  Phi-4-reasoningMicrosoft | cross-developer peerstext |
DeepSeek-R1DeepSeek | vs | DeepSeek-V4-Pro-BaseDeepSeek | family variantstext |
| vs | DeepSeek-R1DeepSeek | cross-developer peerstext | |
| vs | DeepSeek-R1DeepSeek | cross-developer peerstext | |
DeepSeek-R1DeepSeek | vs | DeepSeek-V3DeepSeek | family variantstext |
DeepSeek-R1DeepSeek | vs | DeepSeek-V3.2DeepSeek | family variantstext |
DeepSeek-R1DeepSeek | vs |  Llama-3.1-405BMeta | cross-developer peerstext |
DeepSeek-R1DeepSeek | vs | cross-developer peerstext | |
DeepSeek-R1DeepSeek | vs |  GLM-5Z.ai | cross-developer peerstext |
DeepSeek-R1DeepSeek | vs | GLM-5.1Z.ai | cross-developer peerstext |
Primary Evidence
Sources and Freshness
Questions
DeepSeek R1 vs Kimi K2 Thinking FAQs
Is DeepSeek R1 or Kimi K2 Thinking better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both DeepSeek R1 and Kimi K2 Thinking, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, DeepSeek R1 or Kimi K2 Thinking?+
DeepSeek R1 is $0.70 and Kimi K2 Thinking is $0.60 per million tokens, so Kimi K2 Thinking is cheaper on this metric. DeepSeek R1 is $2.50 and Kimi K2 Thinking is $2.50 per million tokens, so they are tied on this metric.
Which has a larger context window, DeepSeek R1 or Kimi K2 Thinking?+
Kimi K2 Thinking has the larger sourced context window. DeepSeek R1 supports 163,840 tokens and Kimi K2 Thinking supports 262,144 tokens.
Which performs better in benchmarks, DeepSeek R1 or Kimi K2 Thinking?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can DeepSeek R1 or Kimi K2 Thinking be self-hosted?+
Both models have the same sourced self-hosting status: supported. DeepSeek R1 is open weight; Kimi K2 Thinking is open weight.
Can DeepSeek R1 and Kimi K2 Thinking understand images?+
DeepSeek R1 is not documented with image input; Kimi K2 Thinking is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, DeepSeek R1 or Kimi K2 Thinking?+
Kimi K2 Thinking has the larger sourced maximum output. DeepSeek R1 supports 32,768 tokens and Kimi K2 Thinking supports 131,072 tokens.
Do DeepSeek R1 and Kimi K2 Thinking support reasoning and tool use?+
DeepSeek R1: reasoning. Kimi K2 Thinking: reasoning and tool calling. Feature support does not establish relative quality.
Which is available from more inference providers, DeepSeek R1 or Kimi K2 Thinking?+
DeepSeek R1 has 2 sourced provider routes; Kimi K2 Thinking has 2, a tie.
Which offers better value, DeepSeek R1 or Kimi K2 Thinking?+
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.