Model comparison
DeepSeek LLM 2.0 vs Kimi K2.7 Code
Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek LLM 2.0 #89 (Estimated); Kimi K2.7 Code #87 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek LLM 2.0 and Kimi K2.7 Code share 0 comparable benchmark results. 0 of 8 categories are comparable. 0 results are unique to DeepSeek LLM 2.0; 23 to Kimi K2.7 Code.
Updated July 23, 2026- Shared results
- 0
- DeepSeek LLM 2.0 only
- 0
- Kimi K2.7 Code only
- 23
- Comparable categories
- 0 / 8
Benchmark data for DeepSeek LLM 2.0 and Kimi K2.7 Code is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 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 does not have sourced benchmark coverage for DeepSeek LLM 2.0 yet. This comparison is currently limited to metadata such as context window, reasoning mode, and pricing where available.
Kimi K2.7 Code is priced at $0.95 input / $4.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for DeepSeek LLM 2.0. Kimi K2.7 Code has the larger context window at 256K, compared with 128K for DeepSeek LLM 2.0.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek LLM 2.0 | Kimi K2.7 Code | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek LLM 2.0$0 input / $0 output | Kimi K2.7 Code$0.95 input / $4 output | DeepSeek LLM 2.0 has the lower combined listed price. |
| Generation speedtokens per second | DeepSeek LLM 2.0Not available | Kimi K2.7 CodeNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek LLM 2.0Not available | Kimi K2.7 CodeNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek LLM 2.0128K | Kimi K2.7 Code256K | Kimi K2.7 Code lists the larger context window. |
Benchmark Deep Dive
Agentic7 benchmarks
| Benchmark | DeepSeek LLM 2.0 | Kimi K2.7 Code | Result |
|---|---|---|---|
| Kimi Claw 24/7Source | — | 46.9% | Not comparable |
| MCP AtlasSource | — | 76% | Not comparable |
| MCP Mark VerifiedSource | — | 81.1% | Not comparable |
| AA Agentic IndexSource | — | 29.6% | Not comparable |
| τ²-bench resultsSource | — | 90.1% | Not comparable |
| GDPval-AASource | — | 34.3% | Not comparable |
| GDPval-AASource | — | 1187 | Not comparable |
Coding6 benchmarks
Reasoning2 benchmarks
Knowledge6 benchmarks
| Benchmark | DeepSeek LLM 2.0 | Kimi K2.7 Code | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | — | 42.0% | Not comparable |
| AA-GPQA DiamondSource | — | 89.6% | Not comparable |
| AA-HLESource | — | 32.8% | Not comparable |
| AA-Omniscience IndexSource | — | -10.7% | Not comparable |
| AA-Omniscience AccuracySource | — | 38.6% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 80.3% | Not comparable |
Multimodal1 benchmarks
| Benchmark | DeepSeek LLM 2.0 | Kimi K2.7 Code | Result |
|---|---|---|---|
| Design Arena WebsiteSource | — | 1302 | Not comparable |
Inst. Following1 benchmarks
| Benchmark | DeepSeek LLM 2.0 | Kimi K2.7 Code | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 63.1% | Not comparable |
Frequently Asked Questions (3)
Can I compare DeepSeek LLM 2.0 and Kimi K2.7 Code 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 LLM 2.0 and Kimi K2.7 Code today?
DeepSeek LLM 2.0: $0.00 input / $0.00 output per 1M tokens Kimi K2.7 Code: $0.95 input / $4.00 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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