Model comparison
Kimi K3 vs Qwen2.5-VL 72B Instruct
Kimi K3 is the stronger model overall, scoring 59.5 to 29.9 on the Noometry Index.
Last verified . 0 shared benchmarks.
Alibaba (Qwen)Summary
- The widest gap is in reasoning, where Kimi K3 leads 63.0 to 20.7.
- Qwen2.5-VL 72B Instruct is cheaper at $2.80 / $8.40 per million input/output tokens, against $3 / $15 for Kimi K3.
- Kimi K3 accepts more context: 1.05M tokens versus 131K.
Side by side
| Kimi K3 | Qwen2.5-VL 72B Instruct | |
|---|---|---|
| Provider | Moonshot AI | Alibaba (Qwen) |
| Noometry Index | 59.5 | 29.9 |
| Released | 2026-07-16 | 2024-09 |
| Weights | Open | Open |
| Context window | 1.05M | 131K |
| Max output | 1.05M | 8K |
| Input $ / M tokens | $3 | $2.80 |
| Output $ / M tokens | $15 | $8.40 |
| Results tracked | 53 | 6 |
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Category by category
Coding Not comparable
Kimi K3: 61.0 (#10), Qwen2.5-VL 72B Instruct: —
| Benchmark | Kimi K3 | Qwen2.5-VL 72B Instruct |
|---|---|---|
| DeepSWE | 68.5% | — |
| FrontierCode | 44.2% | — |
| LMArena WebDev | 1654 | — |
| FrontierSWE | 25.9% | — |
| SciCode | 59.5% | — |
| WeirdML | 82.6% | — |
| LMArena Coding | 1508 | — |
| ALE-Bench | 1,524 | — |
Agentic & Tool Use Kimi K3 leads
Kimi K3: 41.8 (#20), Qwen2.5-VL 72B Instruct: 18.6 (#144)
| Benchmark | Kimi K3 | Qwen2.5-VL 72B Instruct |
|---|---|---|
| APEX-Agents | 50.6% | — |
| τ²-bench Banking | 37.1% | — |
| OSWorld | — | 5% |
| PostTrainBench | 32% | — |
| GBAEval | 48.3% | — |
| GDP.pdf | 19% | — |
| Vending-Bench 2 | 5,165 | — |
Reasoning Kimi K3 leads
Kimi K3: 63.0 (#17), Qwen2.5-VL 72B Instruct: 20.7 (#233)
| Benchmark | Kimi K3 | Qwen2.5-VL 72B Instruct |
|---|---|---|
| ARC-AGI-2 | 60.4% | — |
| SimpleBench | 60.7% | — |
| Kagi LLM Benchmark | — | 36% |
| NYT Connections (extended) | 93.6% | — |
| ARC-AGI-1 | 94.5% | — |
| CritPt | 23.4% | — |
| Chess Puzzles | 39% | — |
| LMArena Hard Prompts | 1496 | — |
| Mystery Game Puzzles | 26% | — |
| DTBench | 91.2% | — |
| LMCA | 52.7% | — |
| Surface Evolver Bench | 95% | — |
| Epoch Capabilities Index | 157.45 | — |
| ForecastBench | 61.1 | — |
Math Not comparable
Kimi K3: 74.2 (#16), Qwen2.5-VL 72B Instruct: —
| Benchmark | Kimi K3 | Qwen2.5-VL 72B Instruct |
|---|---|---|
| FrontierMath (Tiers 1-3) | 72.2% | — |
| FrontierMath Tier 4 | 39% | — |
| MathArena Final-Answer Competitions | 87.8% | — |
| OTIS Mock AIME 2024-2025 | 97.2% | — |
| ProofBench | 87% | — |
| LMArena Math | 1491 | — |
Knowledge Not comparable
Kimi K3: 63.2 (#21), Qwen2.5-VL 72B Instruct: —
| Benchmark | Kimi K3 | Qwen2.5-VL 72B Instruct |
|---|---|---|
| GPQA Diamond | 93.1% | — |
| SimpleQA Verified | 50.6% | — |
| LMArena Expert | 1521 | — |
Multimodal Kimi K3 leads
Kimi K3: 37.8 (#70), Qwen2.5-VL 72B Instruct: 33.5 (#97)
| Benchmark | Kimi K3 | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Vision | — | 1107 |
| Video-MME | — | 73.5% |
| GeoBench | — | 62% |
| Blueprint-Bench 2 | 29.5% | — |
| Furniture Assembly | 34.2% | — |
| SpatialViz-Bench | — | 33.3% |
Multilingual Not comparable
Kimi K3: 56.3 (#21), Qwen2.5-VL 72B Instruct: —
| Benchmark | Kimi K3 | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Non-English | 1466 | — |
| LMArena Chinese | 1529 | — |
| LMArena French | 1491 | — |
| LMArena German | 1488 | — |
| LMArena Japanese | 1487 | — |
| LMArena Korean | 1458 | — |
| LMArena Russian | 1482 | — |
| LMArena Spanish | 1472 | — |
Instruction Following Not comparable
Kimi K3: 77.7 (#14), Qwen2.5-VL 72B Instruct: —
| Benchmark | Kimi K3 | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Instruction Following | 1483 | — |
Long Context Not comparable
Kimi K3: 45.8 (#29), Qwen2.5-VL 72B Instruct: —
| Benchmark | Kimi K3 | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Longer Query | 1494 | — |
Writing & Preference Not comparable
Kimi K3: 76.6 (#4), Qwen2.5-VL 72B Instruct: —
| Benchmark | Kimi K3 | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Text | 1476 | — |
| LMArena Creative Writing | 1454 | — |
| EQ-Bench Creative Writing | 2082 | — |
| EQ-Bench 4 | 1339 | — |
| LMArena Multi-Turn | 1488 | — |
Frequently asked questions
Is Kimi K3 better than Qwen2.5-VL 72B Instruct?
Kimi K3 is the stronger model overall, scoring 59.5 to 29.9 on the Noometry Index.
Which is cheaper, Kimi K3 or Qwen2.5-VL 72B Instruct?
Qwen2.5-VL 72B Instruct is cheaper. It lists at $2.80 per million input tokens and $8.40 per million output tokens; Kimi K3 lists at $3 and $15.
Which has the bigger context window?
Kimi K3 does, with 1.05M tokens against 131K.
How many benchmarks do Kimi K3 and Qwen2.5-VL 72B Instruct share?
0 benchmarks have published results for both models. Kimi K3 has 53 scored results on Noometry and Qwen2.5-VL 72B Instruct has 6.