Model comparison
DeepSeek-R1 vs Kimi K2
Head-to-head evidence from 11 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek-R1 #103 (Supported); Kimi K2 #189 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek-R1 and Kimi K2 share 11 comparable benchmark results. 0 of 8 categories are comparable. 0 results are unique to DeepSeek-R1; 3 to Kimi K2.
Updated July 20, 2026- Shared results
- 11
- DeepSeek-R1 only
- 0
- Kimi K2 only
- 3
- Comparable categories
- 0 / 8
Benchmark data for DeepSeek-R1 and Kimi K2 is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 11 shared benchmark results across 5 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.
Kimi K2 is priced at $0.60 input / $2.50 output per 1M tokens, versus $0.55 input / $2.19 output per 1M tokens for DeepSeek-R1.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | DeepSeek-R1 | Δ | Kimi K2 |
|---|---|---|---|
| Math | DeepSeek-R1Not measured | MarginNo overlap | Kimi K216.1 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek-R1 | Kimi K2 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek-R1$0.55 input / $2.19 output | Kimi K2$0.6 input / $2.5 output | DeepSeek-R1 has the lower combined listed price. |
| Generation speedtokens per second | DeepSeek-R1Not available | Kimi K243 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek-R1Not available | Kimi K21.51 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek-R1128K | Kimi K2128K | Listed context windows are equal. |
Benchmark Deep Dive
Agentic1 benchmarks
| Benchmark | DeepSeek-R1 | Kimi K2 | Result |
|---|---|---|---|
| τ²-bench resultsSource | 36.5% | 61.1% | Kimi K2 leads |
Coding1 benchmarks
| Benchmark | DeepSeek-R1 | Kimi K2 | Result |
|---|---|---|---|
| AA-SciCodeSource | 40.3% | 34.5% | DeepSeek-R1 leads |
Reasoning2 benchmarks
Knowledge6 benchmarks
| Benchmark | DeepSeek-R1 | Kimi K2 | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 20.1% | 19.4% | DeepSeek-R1 leads |
| AA-GPQA DiamondSource | 81.3% | 76.6% | DeepSeek-R1 leads |
| AA-HLESource | 14.9% | 7.0% | DeepSeek-R1 leads |
| AA-Omniscience IndexSource | -27.1% | -27.5% | DeepSeek-R1 leads |
| AA-Omniscience AccuracySource | 31.0% | 26.8% | DeepSeek-R1 leads |
| AA-Omniscience Hallucination RateSource | 84.0% | 74.2% | Kimi K2 leads |
Math2 benchmarks
Multimodal1 benchmarks
| Benchmark | DeepSeek-R1 | Kimi K2 | Result |
|---|---|---|---|
| Design Arena WebsiteSource | — | 1083 | Not comparable |
Inst. Following1 benchmarks
| Benchmark | DeepSeek-R1 | Kimi K2 | Result |
|---|---|---|---|
| AA-IFBenchSource | 39.6% | 41.5% | Kimi K2 leads |
Frequently Asked Questions (3)
Can I compare DeepSeek-R1 and Kimi K2 on BenchLM yet?
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
Why does this comparison show “coming soon”?
BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.
What data is available for DeepSeek-R1 and Kimi K2 today?
DeepSeek-R1: $0.55 input / $2.19 output per 1M tokens Kimi K2: $0.60 input / $2.50 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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