Model comparison
Kimi K3 vs Qwen2.5 14B Instruct
Kimi K3 has enough public results to be ranked (#15); Qwen2.5 14B Instruct does not yet, so treat this comparison as directional.
Last verified . 0 shared benchmarks.
Alibaba (Qwen)Summary
- The widest gap is in coding, where Kimi K3 leads 61.0 to 37.7.
- Qwen2.5 14B Instruct is cheaper at $0.35 / $1.40 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 14B Instruct | |
|---|---|---|
| Provider | Moonshot AI | Alibaba (Qwen) |
| Noometry Index | 59.5 | 38.7 |
| Released | 2026-07-16 | 2024-09 |
| Weights | Open | Open |
| Context window | 1.05M | 131K |
| Max output | 1.05M | 8K |
| Input $ / M tokens | $3 | $0.35 |
| Output $ / M tokens | $15 | $1.40 |
| Results tracked | 53 | 3 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding Kimi K3 leads
Kimi K3: 61.0 (#10), Qwen2.5 14B Instruct: 37.7 (#191)
| Benchmark | Kimi K3 | Qwen2.5 14B Instruct |
|---|---|---|
| DeepSWE | 68.5% | — |
| FrontierCode | 44.2% | — |
| LMArena WebDev | 1654 | — |
| FrontierSWE | 25.9% | — |
| SciCode | 59.5% | — |
| WeirdML | 82.6% | — |
| BigCodeBench Instruct | — | 39.8% |
| LMArena Coding | 1508 | — |
| BigCodeBench Complete | — | 52.2% |
| ALE-Bench | 1,524 | — |
Agentic & Tool Use Not comparable
Kimi K3: 41.8 (#20), Qwen2.5 14B Instruct: —
| Benchmark | Kimi K3 | Qwen2.5 14B Instruct |
|---|---|---|
| APEX-Agents | 50.6% | — |
| τ²-bench Banking | 37.1% | — |
| PostTrainBench | 32% | — |
| GBAEval | 48.3% | — |
| GDP.pdf | 19% | — |
| Vending-Bench 2 | 5,165 | — |
Reasoning Not comparable
Kimi K3: 63.0 (#17), Qwen2.5 14B Instruct: —
| Benchmark | Kimi K3 | Qwen2.5 14B Instruct |
|---|---|---|
| ARC-AGI-2 | 60.4% | — |
| SimpleBench | 60.7% | — |
| 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 14B Instruct: —
| Benchmark | Kimi K3 | Qwen2.5 14B 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 14B Instruct: —
| Benchmark | Kimi K3 | Qwen2.5 14B Instruct |
|---|---|---|
| GPQA Diamond | 93.1% | — |
| SimpleQA Verified | 50.6% | — |
| LMArena Expert | 1521 | — |
| MMLU | — | 79.9% |
Multimodal Not comparable
Kimi K3: 37.8 (#70), Qwen2.5 14B Instruct: —
| Benchmark | Kimi K3 | Qwen2.5 14B Instruct |
|---|---|---|
| Blueprint-Bench 2 | 29.5% | — |
| Furniture Assembly | 34.2% | — |
Multilingual Not comparable
Kimi K3: 56.3 (#21), Qwen2.5 14B Instruct: —
| Benchmark | Kimi K3 | Qwen2.5 14B 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 14B Instruct: —
| Benchmark | Kimi K3 | Qwen2.5 14B Instruct |
|---|---|---|
| LMArena Instruction Following | 1483 | — |
Long Context Not comparable
Kimi K3: 45.8 (#29), Qwen2.5 14B Instruct: —
| Benchmark | Kimi K3 | Qwen2.5 14B Instruct |
|---|---|---|
| LMArena Longer Query | 1494 | — |
Writing & Preference Not comparable
Kimi K3: 76.6 (#4), Qwen2.5 14B Instruct: —
| Benchmark | Kimi K3 | Qwen2.5 14B 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 14B Instruct?
Kimi K3 has enough public results to be ranked (#15); Qwen2.5 14B Instruct does not yet, so treat this comparison as directional.
Which is cheaper, Kimi K3 or Qwen2.5 14B Instruct?
Qwen2.5 14B Instruct is cheaper. It lists at $0.35 per million input tokens and $1.40 per million output tokens; Kimi K3 lists at $3 and $15.
Is Kimi K3 or Qwen2.5 14B Instruct better for coding?
Kimi K3 scores higher on coding benchmarks: 61.0 versus 37.7 in the Noometry coding category.
Which has the bigger context window?
Kimi K3 does, with 1.05M tokens against 131K.
How many benchmarks do Kimi K3 and Qwen2.5 14B Instruct share?
0 benchmarks have published results for both models. Kimi K3 has 53 scored results on Noometry and Qwen2.5 14B Instruct has 3.