Model comparison
GPT-5 Mini vs Kimi K2.5
Kimi K2.5 is the stronger model overall, scoring 48.1 to 41.8 on the Noometry Index.
Last verified . 42 shared benchmarks.
Summary
- They share 42 benchmarks with published results for both. GPT-5 Mini scores higher in 1 category and Kimi K2.5 in 9 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in long context, where Kimi K2.5 leads 52.1 to 41.9.
- The biggest single-benchmark swing is SWE-bench Multilingual: 39.7% for GPT-5 Mini and 67.3% for Kimi K2.5.
- GPT-5 Mini is cheaper at $0.25 / $2 per million input/output tokens, against $0.45 / $2.25 for Kimi K2.5.
- GPT-5 Mini accepts more context: 400K tokens versus 262K.
- Kimi K2.5 has downloadable open weights; the other is API-only.
Side by side
| GPT-5 Mini | Kimi K2.5 | |
|---|---|---|
| Provider | OpenAI | Moonshot AI |
| Noometry Index | 41.8 | 48.1 |
| Released | 2025-08-07 | 2026-01-27 |
| Weights | Proprietary | Open |
| Context window | 400K | 262K |
| Max output | 128K | 262K |
| Input $ / M tokens | $0.25 | $0.45 |
| Output $ / M tokens | $2 | $2.25 |
| Results tracked | 60 | 51 |
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Category by category
Coding Kimi K2.5 leads
GPT-5 Mini: 40.1 (#146), Kimi K2.5: 48.8 (#53)
| Benchmark | GPT-5 Mini | Kimi K2.5 |
|---|---|---|
| SWE-bench Verified | 64.7% | 73.8% |
| SWE-bench Verified (bash only) | 59.8% | 70.8% |
| SWE-bench Multilingual | 39.7% | 67.3% |
| SciCode | 39.2% | 49% |
| WeirdML | 52.7% | 45.6% |
| LMArena Coding | 1406 | 1474 |
| ALE-Bench | 799.77 | 821.65 |
| LMArena WebDev | — | 1437 |
| AlgoTune | 1.38 | — |
Agentic & Tool Use Kimi K2.5 leads
GPT-5 Mini: 31.1 (#70), Kimi K2.5: 34.2 (#48)
| Benchmark | GPT-5 Mini | Kimi K2.5 |
|---|---|---|
| Terminal-Bench | 34.8% | 43.2% |
| Vending-Bench 2 | -31.18 | 1,198 |
| Berkeley Function Calling Leaderboard | 55.5% | — |
| OSWorld | — | 63.3% |
Reasoning Kimi K2.5 leads
GPT-5 Mini: 23.9 (#168), Kimi K2.5: 31.2 (#80)
| Benchmark | GPT-5 Mini | Kimi K2.5 |
|---|---|---|
| ARC-AGI-2 | 4.4% | 11.8% |
| Kagi LLM Benchmark | 70.3% | 78.5% |
| ARC-AGI-1 | 54.3% | 65.3% |
| CritPt | 0% | 3.1% |
| Chess Puzzles | 30% | 12% |
| EnigmaEval | 8.2% | 3.4% |
| LMArena Hard Prompts | 1380 | 1453 |
| Epoch Capabilities Index | 145.52 | 148.03 |
| SimpleBench | — | 46.8% |
| NYT Connections (extended) | — | 69.9% |
| Thematic Generalization | — | 69.4% |
| Mystery Game Puzzles | 10% | — |
| DTBench | 80.5% | — |
| LMCA | 34.2% | — |
| ForecastBench | 61 | — |
Math Kimi K2.5 leads
GPT-5 Mini: 46.7 (#69), Kimi K2.5: 51.8 (#53)
| Benchmark | GPT-5 Mini | Kimi K2.5 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 86.7% | 92.2% |
| LMArena Math | 1378 | 1470 |
| FrontierMath (Feb 2025 set) | 27.2% | 27.9% |
| FrontierMath Tier 4 (v1) | 6.3% | 4.2% |
| FrontierMath (Tiers 1-3) | 46.7% | — |
| FrontierMath Tier 4 | 12.2% | — |
| MathArena Final-Answer Competitions | — | 62.3% |
| ProofBench | 9% | — |
| Omni-MATH | 72.2% | — |
| MATH Level 5 | 97.8% | — |
Knowledge Kimi K2.5 leads
GPT-5 Mini: 45.6 (#86), Kimi K2.5: 53.6 (#56)
| Benchmark | GPT-5 Mini | Kimi K2.5 |
|---|---|---|
| GPQA Diamond | 75% | 87.6% |
| Humanity's Last Exam | 19.4% | 24.4% |
| SimpleQA Verified | 21.6% | 34.3% |
| Vectara Hallucination Rate | 12.9% | 14.2% |
| LMArena Expert | 1379 | 1466 |
| MMLU-Pro | 83.5% | — |
| Confabulations | 13.3% | — |
| GPQA (HELM) | 75.6% | — |
Multimodal Kimi K2.5 leads
GPT-5 Mini: 35.6 (#85), Kimi K2.5: 41.1 (#39)
| Benchmark | GPT-5 Mini | Kimi K2.5 |
|---|---|---|
| LMArena Vision | 1202 | 1269 |
| VPCT | 40.2% | — |
| LMArena Document | — | 1430 |
Multilingual Kimi K2.5 leads
GPT-5 Mini: 48.9 (#137), Kimi K2.5: 53.9 (#53)
| Benchmark | GPT-5 Mini | Kimi K2.5 |
|---|---|---|
| LMArena Non-English | 1363 | 1433 |
| LMArena Chinese | 1385 | 1495 |
| LMArena French | 1386 | 1454 |
| LMArena German | 1366 | 1441 |
| LMArena Japanese | 1341 | 1421 |
| LMArena Korean | 1308 | 1410 |
| LMArena Russian | 1362 | 1435 |
| LMArena Spanish | 1355 | 1450 |
Instruction Following Too close to call
GPT-5 Mini: 76.2 (#46), Kimi K2.5: 75.3 (#64)
| Benchmark | GPT-5 Mini | Kimi K2.5 |
|---|---|---|
| LMArena Instruction Following | 1357 | 1431 |
| IFEval | 92.7% | — |
Long Context Kimi K2.5 leads
GPT-5 Mini: 41.9 (#132), Kimi K2.5: 52.1 (#7)
| Benchmark | GPT-5 Mini | Kimi K2.5 |
|---|---|---|
| Fiction.LiveBench | 69.4% | 86.1% |
| LMArena Longer Query | 1355 | 1445 |
| CL-bench | — | 19.3% |
| CL-bench Life | — | 13.2% |
Writing & Preference Kimi K2.5 leads
GPT-5 Mini: 55.2 (#148), Kimi K2.5: 65.1 (#53)
| Benchmark | GPT-5 Mini | Kimi K2.5 |
|---|---|---|
| LMArena Text | 1373 | 1445 |
| LMArena Creative Writing | 1325 | 1423 |
| EQ-Bench Creative Writing | 1313 | 1579 |
| LMArena Multi-Turn | 1363 | 1444 |
| Short-Story Creative Writing | 83.1% | — |
| WildBench | 85.5% | — |
Frequently asked questions
Is GPT-5 Mini better than Kimi K2.5?
Kimi K2.5 is the stronger model overall, scoring 48.1 to 41.8 on the Noometry Index.
Which is cheaper, GPT-5 Mini or Kimi K2.5?
GPT-5 Mini is cheaper. It lists at $0.25 per million input tokens and $2 per million output tokens; Kimi K2.5 lists at $0.45 and $2.25.
Is GPT-5 Mini or Kimi K2.5 better for coding?
Kimi K2.5 scores higher on coding benchmarks: 48.8 versus 40.1 in the Noometry coding category.
Which has the bigger context window?
GPT-5 Mini does, with 400K tokens against 262K.
How many benchmarks do GPT-5 Mini and Kimi K2.5 share?
42 benchmarks have published results for both models. GPT-5 Mini has 60 scored results on Noometry and Kimi K2.5 has 51.