Model comparison
DeepSeek-V3.1-Terminus vs Kimi K2.7 Code
DeepSeek-V3.1-Terminus and Kimi K2.7 Code score almost the same on the Noometry Index (43.1 vs 43.3), so choose on price, context window or the category you care about most.
Last verified . 3 shared benchmarks.
DeepSeekSummary
- They share 3 benchmarks with published results for both. DeepSeek-V3.1-Terminus scores higher in 0 categories and Kimi K2.7 Code in 3 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in math, where Kimi K2.7 Code leads 52.9 to 38.5.
- The biggest single-benchmark swing is CritPt: 1.7% for DeepSeek-V3.1-Terminus and 10% for Kimi K2.7 Code.
- DeepSeek-V3.1-Terminus is cheaper at $0.27 / $1 per million input/output tokens, against $0.95 / $4 for Kimi K2.7 Code.
- Kimi K2.7 Code accepts more context: 262K tokens versus 164K.
Side by side
| DeepSeek-V3.1-Terminus | Kimi K2.7 Code | |
|---|---|---|
| Provider | DeepSeek | Moonshot AI |
| Noometry Index | 43.1 | 43.3 |
| Released | 2025-09-22 | 2026-06-12 |
| Weights | Open | Open |
| Context window | 164K | 262K |
| Max output | 147K | 262K |
| Input $ / M tokens | $0.27 | $0.95 |
| Output $ / M tokens | $1 | $4 |
| Results tracked | 16 | 19 |
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Category by category
Coding Too close to call
DeepSeek-V3.1-Terminus: 42.0 (#113), Kimi K2.7 Code: 42.9 (#95)
| Benchmark | DeepSeek-V3.1-Terminus | Kimi K2.7 Code |
|---|---|---|
| SciCode | 40.6% | 47.5% |
| ALE-Bench | 745.17 | 886.23 |
| DeepSWE | — | 30.5% |
| FrontierCode | — | 30.1% |
| LMArena WebDev | — | 1473 |
| WeirdML | — | 54.1% |
| LMArena Coding | 1426 | — |
Agentic & Tool Use Not comparable
DeepSeek-V3.1-Terminus: —, Kimi K2.7 Code: 24.0 (#122)
| Benchmark | DeepSeek-V3.1-Terminus | Kimi K2.7 Code |
|---|---|---|
| APEX-Agents | — | 37.6% |
| GBAEval | — | 0.9% |
| Vending-Bench 2 | — | 5,083 |
Reasoning Kimi K2.7 Code leads
DeepSeek-V3.1-Terminus: 26.4 (#133), Kimi K2.7 Code: 39.0 (#61)
| Benchmark | DeepSeek-V3.1-Terminus | Kimi K2.7 Code |
|---|---|---|
| CritPt | 1.7% | 10% |
| SimpleBench | — | 57.9% |
| Kagi LLM Benchmark | 57.4% | — |
| Chess Puzzles | — | 21% |
| LMArena Hard Prompts | 1426 | — |
| DTBench | 81.3% | — |
| LMCA | 28.6% | — |
| Surface Evolver Bench | — | 48.8% |
| Epoch Capabilities Index | — | 149.97 |
Math Kimi K2.7 Code leads
DeepSeek-V3.1-Terminus: 38.5 (#137), Kimi K2.7 Code: 52.9 (#48)
| Benchmark | DeepSeek-V3.1-Terminus | Kimi K2.7 Code |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 54% |
| FrontierMath Tier 4 | — | 12.2% |
| OTIS Mock AIME 2024-2025 | — | 95.6% |
| LMArena Math | 1402 | — |
Knowledge Not comparable
DeepSeek-V3.1-Terminus: —, Kimi K2.7 Code: 53.5 (#57)
| Benchmark | DeepSeek-V3.1-Terminus | Kimi K2.7 Code |
|---|---|---|
| GPQA Diamond | — | 87.9% |
| SimpleQA Verified | — | 36.5% |
Multilingual Not comparable
DeepSeek-V3.1-Terminus: 52.1 (#92), Kimi K2.7 Code: —
| Benchmark | DeepSeek-V3.1-Terminus | Kimi K2.7 Code |
|---|---|---|
| LMArena Non-English | 1407 | — |
| LMArena Russian | 1436 | — |
Instruction Following Not comparable
DeepSeek-V3.1-Terminus: 74.0 (#106), Kimi K2.7 Code: —
| Benchmark | DeepSeek-V3.1-Terminus | Kimi K2.7 Code |
|---|---|---|
| LMArena Instruction Following | 1404 | — |
Long Context Not comparable
DeepSeek-V3.1-Terminus: 43.4 (#97), Kimi K2.7 Code: —
| Benchmark | DeepSeek-V3.1-Terminus | Kimi K2.7 Code |
|---|---|---|
| LMArena Longer Query | 1421 | — |
Writing & Preference Not comparable
DeepSeek-V3.1-Terminus: 61.0 (#92), Kimi K2.7 Code: —
| Benchmark | DeepSeek-V3.1-Terminus | Kimi K2.7 Code |
|---|---|---|
| LMArena Text | 1419 | — |
| LMArena Creative Writing | 1403 | — |
| LMArena Multi-Turn | 1411 | — |
Frequently asked questions
Is DeepSeek-V3.1-Terminus better than Kimi K2.7 Code?
DeepSeek-V3.1-Terminus and Kimi K2.7 Code score almost the same on the Noometry Index (43.1 vs 43.3), so choose on price, context window or the category you care about most.
Which is cheaper, DeepSeek-V3.1-Terminus or Kimi K2.7 Code?
DeepSeek-V3.1-Terminus is cheaper. It lists at $0.27 per million input tokens and $1 per million output tokens; Kimi K2.7 Code lists at $0.95 and $4.
Is DeepSeek-V3.1-Terminus or Kimi K2.7 Code better for coding?
They score almost the same on coding (42.0 vs 42.9); test both on your own repository before choosing.
Which has the bigger context window?
Kimi K2.7 Code does, with 262K tokens against 164K.
How many benchmarks do DeepSeek-V3.1-Terminus and Kimi K2.7 Code share?
3 benchmarks have published results for both models. DeepSeek-V3.1-Terminus has 16 scored results on Noometry and Kimi K2.7 Code has 19.