Model comparison
GPT-3.5-turbo vs Kimi K2 (Jul 2025)
Kimi K2 (Jul 2025) is the stronger model overall, scoring 41.2 to 23.2 on the Noometry Index.
Last verified . 22 shared benchmarks.
Summary
- They share 22 benchmarks with published results for both. GPT-3.5-turbo scores higher in 0 categories and Kimi K2 (Jul 2025) in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Kimi K2 (Jul 2025) leads 62.3 to 25.3.
- The biggest single-benchmark swing is WeirdML: 3.5% for GPT-3.5-turbo and 42.8% for Kimi K2 (Jul 2025).
- GPT-3.5-turbo is cheaper at $0.50 / $1.50 per million input/output tokens, against $0.57 / $2.30 for Kimi K2 (Jul 2025).
- Kimi K2 (Jul 2025) accepts more context: 262K tokens versus 16K.
- Kimi K2 (Jul 2025) has downloadable open weights; the other is API-only.
Side by side
| GPT-3.5-turbo | Kimi K2 (Jul 2025) | |
|---|---|---|
| Provider | OpenAI | Moonshot AI |
| Noometry Index | 23.2 | 41.2 |
| Released | 2023-03-01 | 2025-07-12 |
| Weights | Proprietary | Open |
| Context window | 16K | 262K |
| Max output | 4K | 262K |
| Input $ / M tokens | $0.50 | $0.57 |
| Output $ / M tokens | $1.50 | $2.30 |
| Results tracked | 44 | 42 |
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Category by category
Coding Kimi K2 (Jul 2025) leads
GPT-3.5-turbo: 23.9 (#331), Kimi K2 (Jul 2025): 42.4 (#102)
| Benchmark | GPT-3.5-turbo | Kimi K2 (Jul 2025) |
|---|---|---|
| WeirdML | 3.5% | 42.8% |
| LMArena Coding | 1136 | 1399 |
| SWE-bench Verified (bash only) | — | 63.4% |
| Aider Polyglot | — | 59.1% |
| GSO | — | 4.9% |
| BigCodeBench Instruct | 39.1% | — |
| BigCodeBench Complete | 50.6% | — |
| ALE-Bench | — | 597.5 |
| HumanEval+ | 70.7% | — |
| MBPP+ | 69.7% | — |
Agentic & Tool Use Not comparable
GPT-3.5-turbo: —, Kimi K2 (Jul 2025): 32.4 (#64)
| Benchmark | GPT-3.5-turbo | Kimi K2 (Jul 2025) |
|---|---|---|
| METR Time Horizons | 21.5% | 59.2% |
| Terminal-Bench | — | 35.7% |
| Berkeley Function Calling Leaderboard | — | 59.1% |
Reasoning Kimi K2 (Jul 2025) leads
GPT-3.5-turbo: 13.8 (#332), Kimi K2 (Jul 2025): 23.3 (#179)
| Benchmark | GPT-3.5-turbo | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Hard Prompts | 1108 | 1384 |
| Epoch Capabilities Index | 118.55 | 146.01 |
| ForecastBench | 50.4 | 60.2 |
| SimpleBench | — | 26.3% |
| Kagi LLM Benchmark | — | 64.4% |
| Chess Puzzles | 0% | — |
| Mystery Game Puzzles | 3% | — |
| DTBench | 48.5% | — |
| LMCA | 9.7% | — |
| Adversarial NLI | 58.1% | — |
| BIG-Bench Hard | 61.6% | — |
| CommonsenseQA 2.0 | 57% | — |
| WinoGrande | 81.6% | — |
Math Kimi K2 (Jul 2025) leads
GPT-3.5-turbo: 6.3 (#327), Kimi K2 (Jul 2025): 42.7 (#83)
| Benchmark | GPT-3.5-turbo | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Math | 1142 | 1397 |
| FrontierMath (Tiers 1-3) | 0% | — |
| OTIS Mock AIME 2024-2025 | 2.2% | — |
| Omni-MATH | — | 65.4% |
| MATH Level 5 | 15.9% | — |
| FrontierMath (Feb 2025 set) | — | 21.4% |
| FrontierMath Tier 4 (v1) | — | 0% |
| GSM8K | 57.8% | — |
Knowledge Kimi K2 (Jul 2025) leads
GPT-3.5-turbo: 10.0 (#303), Kimi K2 (Jul 2025): 37.3 (#157)
| Benchmark | GPT-3.5-turbo | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Expert | 1070 | 1365 |
| GPQA Diamond | 28% | — |
| MMLU-Pro | — | 81.9% |
| Confabulations | — | 20.4% |
| Vectara Hallucination Rate | — | 17.9% |
| GPQA (HELM) | — | 65.3% |
| ARC (AI2) Challenge | 87.4% | — |
| BoolQ | 87% | — |
| MMLU | 71.4% | — |
| OpenBookQA | 86% | — |
| TriviaQA | 85.8% | — |
Multilingual Kimi K2 (Jul 2025) leads
GPT-3.5-turbo: 31.5 (#258), Kimi K2 (Jul 2025): 49.6 (#130)
| Benchmark | GPT-3.5-turbo | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Non-English | 1108 | 1372 |
| LMArena Chinese | 1075 | 1415 |
| LMArena French | 1118 | 1379 |
| LMArena German | 1090 | 1387 |
| LMArena Japanese | 1043 | 1349 |
| LMArena Korean | 1019 | 1325 |
| LMArena Russian | 1123 | 1385 |
| LMArena Spanish | 1121 | 1386 |
Instruction Following Kimi K2 (Jul 2025) leads
GPT-3.5-turbo: 57.9 (#262), Kimi K2 (Jul 2025): 71.1 (#156)
| Benchmark | GPT-3.5-turbo | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Instruction Following | 1119 | 1348 |
| IFEval | — | 85% |
Long Context Kimi K2 (Jul 2025) leads
GPT-3.5-turbo: 34.0 (#254), Kimi K2 (Jul 2025): 41.2 (#145)
| Benchmark | GPT-3.5-turbo | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Longer Query | 1121 | 1353 |
| Fiction.LiveBench | — | 66.7% |
| CL-bench | — | 17.6% |
Writing & Preference Kimi K2 (Jul 2025) leads
GPT-3.5-turbo: 25.3 (#305), Kimi K2 (Jul 2025): 62.3 (#78)
| Benchmark | GPT-3.5-turbo | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Text | 1125 | 1380 |
| LMArena Creative Writing | 1092 | 1350 |
| EQ-Bench Creative Writing | 451 | 1666 |
| LMArena Multi-Turn | 1117 | 1371 |
| Short-Story Creative Writing | — | 85.6% |
| WildBench | — | 86.2% |
Frequently asked questions
Is GPT-3.5-turbo better than Kimi K2 (Jul 2025)?
Kimi K2 (Jul 2025) is the stronger model overall, scoring 41.2 to 23.2 on the Noometry Index.
Which is cheaper, GPT-3.5-turbo or Kimi K2 (Jul 2025)?
GPT-3.5-turbo is cheaper. It lists at $0.50 per million input tokens and $1.50 per million output tokens; Kimi K2 (Jul 2025) lists at $0.57 and $2.30.
Is GPT-3.5-turbo or Kimi K2 (Jul 2025) better for coding?
Kimi K2 (Jul 2025) scores higher on coding benchmarks: 42.4 versus 23.9 in the Noometry coding category.
Which has the bigger context window?
Kimi K2 (Jul 2025) does, with 262K tokens against 16K.
How many benchmarks do GPT-3.5-turbo and Kimi K2 (Jul 2025) share?
22 benchmarks have published results for both models. GPT-3.5-turbo has 44 scored results on Noometry and Kimi K2 (Jul 2025) has 42.