Model comparison
GPT-4.1 mini vs Kimi K2.7 Code
Kimi K2.7 Code is the stronger model overall, scoring 43.3 to 33.6 on the Noometry Index. GPT-4.1 mini costs 2.4× less per token, which makes it the better buy when Kimi K2.7 Code's lead doesn't matter for your workload.
Last verified . 9 shared benchmarks.
Summary
- They share 9 benchmarks with published results for both. GPT-4.1 mini scores higher in 1 category and Kimi K2.7 Code in 4 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in math, where Kimi K2.7 Code leads 52.9 to 24.1.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 44.7% for GPT-4.1 mini and 95.6% for Kimi K2.7 Code.
- GPT-4.1 mini is cheaper at $0.40 / $1.60 per million input/output tokens, against $0.95 / $4 for Kimi K2.7 Code.
- GPT-4.1 mini accepts more context: 1.05M tokens versus 262K.
- Kimi K2.7 Code has downloadable open weights; the other is API-only.
Side by side
| GPT-4.1 mini | Kimi K2.7 Code | |
|---|---|---|
| Provider | OpenAI | Moonshot AI |
| Noometry Index | 33.6 | 43.3 |
| Released | 2025-04-14 | 2026-06-12 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 262K |
| Max output | 33K | 262K |
| Input $ / M tokens | $0.40 | $0.95 |
| Output $ / M tokens | $1.60 | $4 |
| Results tracked | 47 | 19 |
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Category by category
Coding Kimi K2.7 Code leads
GPT-4.1 mini: 30.6 (#293), Kimi K2.7 Code: 42.9 (#95)
| Benchmark | GPT-4.1 mini | Kimi K2.7 Code |
|---|---|---|
| SciCode | 40.4% | 47.5% |
| WeirdML | 37.6% | 54.1% |
| DeepSWE | — | 30.5% |
| FrontierCode | — | 30.1% |
| SWE-bench Verified (bash only) | 23.9% | — |
| Aider Polyglot | 32.4% | — |
| LMArena WebDev | — | 1473 |
| BigCodeBench Instruct | 48.9% | — |
| LMArena Coding | 1367 | — |
| CadEval | 16% | — |
| ALE-Bench | — | 886.23 |
Agentic & Tool Use GPT-4.1 mini leads
GPT-4.1 mini: 33.3 (#55), Kimi K2.7 Code: 24.0 (#122)
| Benchmark | GPT-4.1 mini | Kimi K2.7 Code |
|---|---|---|
| APEX-Agents | — | 37.6% |
| Berkeley Function Calling Leaderboard | 50.5% | — |
| GBAEval | — | 0.9% |
| Vending-Bench 2 | — | 5,083 |
Reasoning Kimi K2.7 Code leads
GPT-4.1 mini: 10.8 (#340), Kimi K2.7 Code: 39.0 (#61)
| Benchmark | GPT-4.1 mini | Kimi K2.7 Code |
|---|---|---|
| CritPt | 0% | 10% |
| Chess Puzzles | 7% | 21% |
| Epoch Capabilities Index | 135.01 | 149.97 |
| ARC-AGI-2 | 0% | — |
| SimpleBench | — | 57.9% |
| Kagi LLM Benchmark | 48.6% | — |
| ARC-AGI-1 | 3.5% | — |
| LMArena Hard Prompts | 1349 | — |
| Mystery Game Puzzles | 7% | — |
| DTBench | 68.8% | — |
| LMCA | 21.1% | — |
| Surface Evolver Bench | — | 48.8% |
Math Kimi K2.7 Code leads
GPT-4.1 mini: 24.1 (#270), Kimi K2.7 Code: 52.9 (#48)
| Benchmark | GPT-4.1 mini | Kimi K2.7 Code |
|---|---|---|
| FrontierMath (Tiers 1-3) | 6.7% | 54% |
| OTIS Mock AIME 2024-2025 | 44.7% | 95.6% |
| FrontierMath Tier 4 | — | 12.2% |
| Omni-MATH | 49.1% | — |
| LMArena Math | 1343 | — |
| MATH Level 5 | 87.3% | — |
| FrontierMath (Feb 2025 set) | 4.5% | — |
Knowledge Kimi K2.7 Code leads
GPT-4.1 mini: 34.7 (#194), Kimi K2.7 Code: 53.5 (#57)
| Benchmark | GPT-4.1 mini | Kimi K2.7 Code |
|---|---|---|
| GPQA Diamond | 65.8% | 87.9% |
| SimpleQA Verified | 12.7% | 36.5% |
| MMLU-Pro | 78.3% | — |
| GPQA (HELM) | 61.4% | — |
| LMArena Expert | 1338 | — |
Multimodal Not comparable
GPT-4.1 mini: 35.8 (#82), Kimi K2.7 Code: —
| Benchmark | GPT-4.1 mini | Kimi K2.7 Code |
|---|---|---|
| LMArena Vision | 1181 | — |
Multilingual Not comparable
GPT-4.1 mini: 45.7 (#166), Kimi K2.7 Code: —
| Benchmark | GPT-4.1 mini | Kimi K2.7 Code |
|---|---|---|
| LMArena Non-English | 1318 | — |
| LMArena Chinese | 1329 | — |
| LMArena French | 1358 | — |
| LMArena German | 1351 | — |
| LMArena Japanese | 1290 | — |
| LMArena Korean | 1298 | — |
| LMArena Russian | 1324 | — |
| LMArena Spanish | 1319 | — |
Instruction Following Not comparable
GPT-4.1 mini: 73.7 (#118), Kimi K2.7 Code: —
| Benchmark | GPT-4.1 mini | Kimi K2.7 Code |
|---|---|---|
| IFEval | 90.4% | — |
| LMArena Instruction Following | 1333 | — |
Long Context Not comparable
GPT-4.1 mini: 31.8 (#275), Kimi K2.7 Code: —
| Benchmark | GPT-4.1 mini | Kimi K2.7 Code |
|---|---|---|
| Fiction.LiveBench | 44.4% | — |
| LMArena Longer Query | 1344 | — |
Writing & Preference Not comparable
GPT-4.1 mini: 48.6 (#199), Kimi K2.7 Code: —
| Benchmark | GPT-4.1 mini | Kimi K2.7 Code |
|---|---|---|
| LMArena Text | 1340 | — |
| LMArena Creative Writing | 1300 | — |
| EQ-Bench Creative Writing | 1147 | — |
| WildBench | 83.8% | — |
| LMArena Multi-Turn | 1354 | — |
Frequently asked questions
Is GPT-4.1 mini better than Kimi K2.7 Code?
Kimi K2.7 Code is the stronger model overall, scoring 43.3 to 33.6 on the Noometry Index. GPT-4.1 mini costs 2.4× less per token, which makes it the better buy when Kimi K2.7 Code's lead doesn't matter for your workload.
Which is cheaper, GPT-4.1 mini or Kimi K2.7 Code?
GPT-4.1 mini is cheaper. It lists at $0.40 per million input tokens and $1.60 per million output tokens; Kimi K2.7 Code lists at $0.95 and $4.
Is GPT-4.1 mini or Kimi K2.7 Code better for coding?
Kimi K2.7 Code scores higher on coding benchmarks: 42.9 versus 30.6 in the Noometry coding category.
Which has the bigger context window?
GPT-4.1 mini does, with 1.05M tokens against 262K.
How many benchmarks do GPT-4.1 mini and Kimi K2.7 Code share?
9 benchmarks have published results for both models. GPT-4.1 mini has 47 scored results on Noometry and Kimi K2.7 Code has 19.