Model comparison
GPT-3.5-turbo vs Kimi K2.7 Code
Kimi K2.7 Code is the stronger model overall, scoring 43.3 to 23.2 on the Noometry Index. GPT-3.5-turbo costs 2.3× less per token, which makes it the better buy when Kimi K2.7 Code's lead doesn't matter for your workload.
Last verified . 6 shared benchmarks.
Summary
- They share 6 benchmarks with published results for both. GPT-3.5-turbo scores higher in 0 categories and Kimi K2.7 Code in 4 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in math, where Kimi K2.7 Code leads 52.9 to 6.3.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 2.2% for GPT-3.5-turbo and 95.6% for Kimi K2.7 Code.
- GPT-3.5-turbo is cheaper at $0.50 / $1.50 per million input/output tokens, against $0.95 / $4 for Kimi K2.7 Code.
- Kimi K2.7 Code accepts more context: 262K tokens versus 16K.
- Kimi K2.7 Code has downloadable open weights; the other is API-only.
Side by side
| GPT-3.5-turbo | Kimi K2.7 Code | |
|---|---|---|
| Provider | OpenAI | Moonshot AI |
| Noometry Index | 23.2 | 43.3 |
| Released | 2023-03-01 | 2026-06-12 |
| Weights | Proprietary | Open |
| Context window | 16K | 262K |
| Max output | 4K | 262K |
| Input $ / M tokens | $0.50 | $0.95 |
| Output $ / M tokens | $1.50 | $4 |
| Results tracked | 44 | 19 |
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Category by category
Coding Kimi K2.7 Code leads
GPT-3.5-turbo: 23.9 (#331), Kimi K2.7 Code: 42.9 (#95)
| Benchmark | GPT-3.5-turbo | Kimi K2.7 Code |
|---|---|---|
| WeirdML | 3.5% | 54.1% |
| DeepSWE | — | 30.5% |
| FrontierCode | — | 30.1% |
| LMArena WebDev | — | 1473 |
| SciCode | — | 47.5% |
| BigCodeBench Instruct | 39.1% | — |
| LMArena Coding | 1136 | — |
| BigCodeBench Complete | 50.6% | — |
| ALE-Bench | — | 886.23 |
| HumanEval+ | 70.7% | — |
| MBPP+ | 69.7% | — |
Agentic & Tool Use Not comparable
GPT-3.5-turbo: —, Kimi K2.7 Code: 24.0 (#122)
| Benchmark | GPT-3.5-turbo | Kimi K2.7 Code |
|---|---|---|
| APEX-Agents | — | 37.6% |
| GBAEval | — | 0.9% |
| METR Time Horizons | 21.5% | — |
| Vending-Bench 2 | — | 5,083 |
Reasoning Kimi K2.7 Code leads
GPT-3.5-turbo: 13.8 (#332), Kimi K2.7 Code: 39.0 (#61)
| Benchmark | GPT-3.5-turbo | Kimi K2.7 Code |
|---|---|---|
| Chess Puzzles | 0% | 21% |
| Epoch Capabilities Index | 118.55 | 149.97 |
| SimpleBench | — | 57.9% |
| CritPt | — | 10% |
| LMArena Hard Prompts | 1108 | — |
| Mystery Game Puzzles | 3% | — |
| DTBench | 48.5% | — |
| LMCA | 9.7% | — |
| Surface Evolver Bench | — | 48.8% |
| Adversarial NLI | 58.1% | — |
| BIG-Bench Hard | 61.6% | — |
| CommonsenseQA 2.0 | 57% | — |
| ForecastBench | 50.4 | — |
| WinoGrande | 81.6% | — |
Math Kimi K2.7 Code leads
GPT-3.5-turbo: 6.3 (#327), Kimi K2.7 Code: 52.9 (#48)
| Benchmark | GPT-3.5-turbo | Kimi K2.7 Code |
|---|---|---|
| FrontierMath (Tiers 1-3) | 0% | 54% |
| OTIS Mock AIME 2024-2025 | 2.2% | 95.6% |
| FrontierMath Tier 4 | — | 12.2% |
| LMArena Math | 1142 | — |
| MATH Level 5 | 15.9% | — |
| GSM8K | 57.8% | — |
Knowledge Kimi K2.7 Code leads
GPT-3.5-turbo: 10.0 (#303), Kimi K2.7 Code: 53.5 (#57)
| Benchmark | GPT-3.5-turbo | Kimi K2.7 Code |
|---|---|---|
| GPQA Diamond | 28% | 87.9% |
| SimpleQA Verified | — | 36.5% |
| LMArena Expert | 1070 | — |
| ARC (AI2) Challenge | 87.4% | — |
| BoolQ | 87% | — |
| MMLU | 71.4% | — |
| OpenBookQA | 86% | — |
| TriviaQA | 85.8% | — |
Multilingual Not comparable
GPT-3.5-turbo: 31.5 (#258), Kimi K2.7 Code: —
| Benchmark | GPT-3.5-turbo | Kimi K2.7 Code |
|---|---|---|
| LMArena Non-English | 1108 | — |
| LMArena Chinese | 1075 | — |
| LMArena French | 1118 | — |
| LMArena German | 1090 | — |
| LMArena Japanese | 1043 | — |
| LMArena Korean | 1019 | — |
| LMArena Russian | 1123 | — |
| LMArena Spanish | 1121 | — |
Instruction Following Not comparable
GPT-3.5-turbo: 57.9 (#262), Kimi K2.7 Code: —
| Benchmark | GPT-3.5-turbo | Kimi K2.7 Code |
|---|---|---|
| LMArena Instruction Following | 1119 | — |
Long Context Not comparable
GPT-3.5-turbo: 34.0 (#254), Kimi K2.7 Code: —
| Benchmark | GPT-3.5-turbo | Kimi K2.7 Code |
|---|---|---|
| LMArena Longer Query | 1121 | — |
Writing & Preference Not comparable
GPT-3.5-turbo: 25.3 (#305), Kimi K2.7 Code: —
| Benchmark | GPT-3.5-turbo | Kimi K2.7 Code |
|---|---|---|
| LMArena Text | 1125 | — |
| LMArena Creative Writing | 1092 | — |
| EQ-Bench Creative Writing | 451 | — |
| LMArena Multi-Turn | 1117 | — |
Frequently asked questions
Is GPT-3.5-turbo better than Kimi K2.7 Code?
Kimi K2.7 Code is the stronger model overall, scoring 43.3 to 23.2 on the Noometry Index. GPT-3.5-turbo costs 2.3× 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-3.5-turbo or Kimi K2.7 Code?
GPT-3.5-turbo is cheaper. It lists at $0.50 per million input tokens and $1.50 per million output tokens; Kimi K2.7 Code lists at $0.95 and $4.
Is GPT-3.5-turbo or Kimi K2.7 Code better for coding?
Kimi K2.7 Code scores higher on coding benchmarks: 42.9 versus 23.9 in the Noometry coding category.
Which has the bigger context window?
Kimi K2.7 Code does, with 262K tokens against 16K.
How many benchmarks do GPT-3.5-turbo and Kimi K2.7 Code share?
6 benchmarks have published results for both models. GPT-3.5-turbo has 44 scored results on Noometry and Kimi K2.7 Code has 19.