Model comparison
GPT-5.3 Chat vs Kimi K2 (Jul 2025)
GPT-5.3 Chat is the stronger model overall, scoring 42.8 to 41.2 on the Noometry Index. Kimi K2 (Jul 2025) costs 4.8× less per token, which makes it the better buy when GPT-5.3 Chat's lead doesn't matter for your workload.
Last verified . 18 shared benchmarks.
Summary
- They share 18 benchmarks with published results for both. GPT-5.3 Chat scores higher in 6 categories and Kimi K2 (Jul 2025) in 2 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-5.3 Chat leads 28.5 to 23.3.
- Kimi K2 (Jul 2025) is cheaper at $0.57 / $2.30 per million input/output tokens, against $1.75 / $14 for GPT-5.3 Chat.
- Kimi K2 (Jul 2025) accepts more context: 262K tokens versus 128K.
- Kimi K2 (Jul 2025) has downloadable open weights; the other is API-only.
Side by side
| GPT-5.3 Chat | Kimi K2 (Jul 2025) | |
|---|---|---|
| Provider | OpenAI | Moonshot AI |
| Noometry Index | 42.8 | 41.2 |
| Released | 2026-03-03 | 2025-07-12 |
| Weights | Proprietary | Open |
| Context window | 128K | 262K |
| Max output | 16K | 262K |
| Input $ / M tokens | $1.75 | $0.57 |
| Output $ / M tokens | $14 | $2.30 |
| Results tracked | 18 | 42 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding Too close to call
GPT-5.3 Chat: 41.4 (#124), Kimi K2 (Jul 2025): 42.4 (#102)
| Benchmark | GPT-5.3 Chat | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Coding | 1408 | 1399 |
| SWE-bench Verified (bash only) | — | 63.4% |
| Aider Polyglot | — | 59.1% |
| GSO | — | 4.9% |
| WeirdML | — | 42.8% |
| ALE-Bench | — | 597.5 |
Agentic & Tool Use Not comparable
GPT-5.3 Chat: —, Kimi K2 (Jul 2025): 32.4 (#64)
| Benchmark | GPT-5.3 Chat | Kimi K2 (Jul 2025) |
|---|---|---|
| Terminal-Bench | — | 35.7% |
| Berkeley Function Calling Leaderboard | — | 59.1% |
| METR Time Horizons | — | 59.2% |
Reasoning GPT-5.3 Chat leads
GPT-5.3 Chat: 28.5 (#102), Kimi K2 (Jul 2025): 23.3 (#179)
| Benchmark | GPT-5.3 Chat | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Hard Prompts | 1399 | 1384 |
| SimpleBench | — | 26.3% |
| Kagi LLM Benchmark | — | 64.4% |
| Epoch Capabilities Index | — | 146.01 |
| ForecastBench | — | 60.2 |
Math Kimi K2 (Jul 2025) leads
GPT-5.3 Chat: 38.2 (#142), Kimi K2 (Jul 2025): 42.7 (#83)
| Benchmark | GPT-5.3 Chat | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Math | 1389 | 1397 |
| Omni-MATH | — | 65.4% |
| FrontierMath (Feb 2025 set) | — | 21.4% |
| FrontierMath Tier 4 (v1) | — | 0% |
Knowledge GPT-5.3 Chat leads
GPT-5.3 Chat: 38.8 (#140), Kimi K2 (Jul 2025): 37.3 (#157)
| Benchmark | GPT-5.3 Chat | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Expert | 1397 | 1365 |
| MMLU-Pro | — | 81.9% |
| Confabulations | — | 20.4% |
| Vectara Hallucination Rate | — | 17.9% |
| GPQA (HELM) | — | 65.3% |
Multilingual Too close to call
GPT-5.3 Chat: 50.3 (#124), Kimi K2 (Jul 2025): 49.6 (#130)
| Benchmark | GPT-5.3 Chat | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Non-English | 1382 | 1372 |
| LMArena Chinese | 1432 | 1415 |
| LMArena French | 1397 | 1379 |
| LMArena German | 1384 | 1387 |
| LMArena Japanese | 1352 | 1349 |
| LMArena Korean | 1346 | 1325 |
| LMArena Russian | 1400 | 1385 |
| LMArena Spanish | 1371 | 1386 |
Instruction Following GPT-5.3 Chat leads
GPT-5.3 Chat: 72.8 (#129), Kimi K2 (Jul 2025): 71.1 (#156)
| Benchmark | GPT-5.3 Chat | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Instruction Following | 1378 | 1348 |
| IFEval | — | 85% |
Long Context GPT-5.3 Chat leads
GPT-5.3 Chat: 42.6 (#120), Kimi K2 (Jul 2025): 41.2 (#145)
| Benchmark | GPT-5.3 Chat | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Longer Query | 1396 | 1353 |
| Fiction.LiveBench | — | 66.7% |
| CL-bench | — | 17.6% |
Writing & Preference Too close to call
GPT-5.3 Chat: 63.1 (#68), Kimi K2 (Jul 2025): 62.3 (#78)
| Benchmark | GPT-5.3 Chat | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Text | 1389 | 1380 |
| LMArena Creative Writing | 1355 | 1350 |
| EQ-Bench Creative Writing | 1690 | 1666 |
| LMArena Multi-Turn | 1412 | 1371 |
| Short-Story Creative Writing | — | 85.6% |
| WildBench | — | 86.2% |
Frequently asked questions
Is GPT-5.3 Chat better than Kimi K2 (Jul 2025)?
GPT-5.3 Chat is the stronger model overall, scoring 42.8 to 41.2 on the Noometry Index. Kimi K2 (Jul 2025) costs 4.8× less per token, which makes it the better buy when GPT-5.3 Chat's lead doesn't matter for your workload.
Which is cheaper, GPT-5.3 Chat or Kimi K2 (Jul 2025)?
Kimi K2 (Jul 2025) is cheaper. It lists at $0.57 per million input tokens and $2.30 per million output tokens; GPT-5.3 Chat lists at $1.75 and $14.
Is GPT-5.3 Chat or Kimi K2 (Jul 2025) better for coding?
They score almost the same on coding (41.4 vs 42.4); test both on your own repository before choosing.
Which has the bigger context window?
Kimi K2 (Jul 2025) does, with 262K tokens against 128K.
How many benchmarks do GPT-5.3 Chat and Kimi K2 (Jul 2025) share?
18 benchmarks have published results for both models. GPT-5.3 Chat has 18 scored results on Noometry and Kimi K2 (Jul 2025) has 42.