Model comparison
GPT-4.1 nano vs Kimi K2.5
Kimi K2.5 is the stronger model overall, scoring 48.1 to 27.9 on the Noometry Index. GPT-4.1 nano costs 5.1× less per token, which makes it the better buy when Kimi K2.5's lead doesn't matter for your workload.
Last verified . 28 shared benchmarks.
Summary
- They share 28 benchmarks with published results for both. GPT-4.1 nano scores higher in 0 categories and Kimi K2.5 in 10 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Kimi K2.5 leads 53.6 to 21.8.
- The biggest single-benchmark swing is ARC-AGI-1: 0% for GPT-4.1 nano and 65.3% for Kimi K2.5.
- GPT-4.1 nano is cheaper at $0.10 / $0.40 per million input/output tokens, against $0.45 / $2.25 for Kimi K2.5.
- GPT-4.1 nano accepts more context: 1.05M tokens versus 262K.
- Kimi K2.5 has downloadable open weights; the other is API-only.
Side by side
| GPT-4.1 nano | Kimi K2.5 | |
|---|---|---|
| Provider | OpenAI | Moonshot AI |
| Noometry Index | 27.9 | 48.1 |
| Released | 2025-04-14 | 2026-01-27 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 262K |
| Max output | 33K | 262K |
| Input $ / M tokens | $0.10 | $0.45 |
| Output $ / M tokens | $0.40 | $2.25 |
| Results tracked | 38 | 51 |
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Category by category
Coding Kimi K2.5 leads
GPT-4.1 nano: 24.1 (#330), Kimi K2.5: 48.8 (#53)
| Benchmark | GPT-4.1 nano | Kimi K2.5 |
|---|---|---|
| SciCode | 25.9% | 49% |
| WeirdML | 19% | 45.6% |
| LMArena Coding | 1306 | 1474 |
| SWE-bench Verified | — | 73.8% |
| SWE-bench Verified (bash only) | — | 70.8% |
| Aider Polyglot | 8.9% | — |
| LMArena WebDev | — | 1437 |
| SWE-bench Multilingual | — | 67.3% |
| ALE-Bench | — | 821.65 |
Agentic & Tool Use Kimi K2.5 leads
GPT-4.1 nano: 26.5 (#104), Kimi K2.5: 34.2 (#48)
| Benchmark | GPT-4.1 nano | Kimi K2.5 |
|---|---|---|
| Terminal-Bench | — | 43.2% |
| Berkeley Function Calling Leaderboard | 33% | — |
| OSWorld | — | 63.3% |
| Vending-Bench 2 | — | 1,198 |
Reasoning Kimi K2.5 leads
GPT-4.1 nano: 8.5 (#349), Kimi K2.5: 31.2 (#80)
| Benchmark | GPT-4.1 nano | Kimi K2.5 |
|---|---|---|
| ARC-AGI-2 | 0% | 11.8% |
| Kagi LLM Benchmark | 33.3% | 78.5% |
| ARC-AGI-1 | 0% | 65.3% |
| CritPt | 0% | 3.1% |
| LMArena Hard Prompts | 1286 | 1453 |
| Epoch Capabilities Index | 129.62 | 148.03 |
| SimpleBench | — | 46.8% |
| NYT Connections (extended) | — | 69.9% |
| Chess Puzzles | — | 12% |
| EnigmaEval | — | 3.4% |
| Thematic Generalization | — | 69.4% |
| DTBench | 52.5% | — |
| LMCA | 5.5% | — |
Math Kimi K2.5 leads
GPT-4.1 nano: 26.9 (#252), Kimi K2.5: 51.8 (#53)
| Benchmark | GPT-4.1 nano | Kimi K2.5 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 28.9% | 92.2% |
| LMArena Math | 1274 | 1470 |
| FrontierMath (Feb 2025 set) | 1% | 27.9% |
| MathArena Final-Answer Competitions | — | 62.3% |
| Omni-MATH | 36.7% | — |
| MATH Level 5 | 70% | — |
| FrontierMath Tier 4 (v1) | — | 4.2% |
Knowledge Kimi K2.5 leads
GPT-4.1 nano: 21.8 (#273), Kimi K2.5: 53.6 (#56)
| Benchmark | GPT-4.1 nano | Kimi K2.5 |
|---|---|---|
| GPQA Diamond | 48.9% | 87.6% |
| SimpleQA Verified | 6% | 34.3% |
| LMArena Expert | 1272 | 1466 |
| Humanity's Last Exam | — | 24.4% |
| MMLU-Pro | 55% | — |
| Vectara Hallucination Rate | — | 14.2% |
| GPQA (HELM) | 50.7% | — |
Multimodal Kimi K2.5 leads
GPT-4.1 nano: 29.2 (#113), Kimi K2.5: 41.1 (#39)
| Benchmark | GPT-4.1 nano | Kimi K2.5 |
|---|---|---|
| LMArena Vision | 1063 | 1269 |
| LMArena Document | — | 1430 |
Multilingual Kimi K2.5 leads
GPT-4.1 nano: 41.6 (#205), Kimi K2.5: 53.9 (#53)
| Benchmark | GPT-4.1 nano | Kimi K2.5 |
|---|---|---|
| LMArena Non-English | 1260 | 1433 |
| LMArena Chinese | 1270 | 1495 |
| LMArena German | 1288 | 1441 |
| LMArena Japanese | 1198 | 1421 |
| LMArena Russian | 1261 | 1435 |
| LMArena French | — | 1454 |
| LMArena Korean | — | 1410 |
| LMArena Spanish | — | 1450 |
Instruction Following Kimi K2.5 leads
GPT-4.1 nano: 67.8 (#193), Kimi K2.5: 75.3 (#64)
| Benchmark | GPT-4.1 nano | Kimi K2.5 |
|---|---|---|
| LMArena Instruction Following | 1267 | 1431 |
| IFEval | 84.3% | — |
Long Context Kimi K2.5 leads
GPT-4.1 nano: 23.7 (#296), Kimi K2.5: 52.1 (#7)
| Benchmark | GPT-4.1 nano | Kimi K2.5 |
|---|---|---|
| Fiction.LiveBench | 25% | 86.1% |
| LMArena Longer Query | 1283 | 1445 |
| CL-bench | — | 19.3% |
| CL-bench Life | — | 13.2% |
Writing & Preference Kimi K2.5 leads
GPT-4.1 nano: 40.5 (#243), Kimi K2.5: 65.1 (#53)
| Benchmark | GPT-4.1 nano | Kimi K2.5 |
|---|---|---|
| LMArena Text | 1285 | 1445 |
| LMArena Creative Writing | 1260 | 1423 |
| EQ-Bench Creative Writing | 946 | 1579 |
| LMArena Multi-Turn | 1277 | 1444 |
| WildBench | 81.2% | — |
Frequently asked questions
Is GPT-4.1 nano better than Kimi K2.5?
Kimi K2.5 is the stronger model overall, scoring 48.1 to 27.9 on the Noometry Index. GPT-4.1 nano costs 5.1× less per token, which makes it the better buy when Kimi K2.5's lead doesn't matter for your workload.
Which is cheaper, GPT-4.1 nano or Kimi K2.5?
GPT-4.1 nano is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; Kimi K2.5 lists at $0.45 and $2.25.
Is GPT-4.1 nano or Kimi K2.5 better for coding?
Kimi K2.5 scores higher on coding benchmarks: 48.8 versus 24.1 in the Noometry coding category.
Which has the bigger context window?
GPT-4.1 nano does, with 1.05M tokens against 262K.
How many benchmarks do GPT-4.1 nano and Kimi K2.5 share?
28 benchmarks have published results for both models. GPT-4.1 nano has 38 scored results on Noometry and Kimi K2.5 has 51.