Model comparison
Kimi K2.5 vs Qwen3 14B
Kimi K2.5 is the stronger model overall, scoring 48.1 to 35.5 on the Noometry Index.
Last verified . 9 shared benchmarks.
Alibaba (Qwen)Summary
- They share 9 benchmarks with published results for both. Kimi K2.5 scores higher in 6 categories and Qwen3 14B in 0 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Kimi K2.5 leads 53.6 to 39.3.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 78.5% for Kimi K2.5 and 49.1% for Qwen3 14B.
- Qwen3 14B is cheaper at $0.35 / $1.40 per million input/output tokens, against $0.45 / $2.25 for Kimi K2.5.
- Kimi K2.5 accepts more context: 262K tokens versus 131K.
Side by side
| Kimi K2.5 | Qwen3 14B | |
|---|---|---|
| Provider | Moonshot AI | Alibaba (Qwen) |
| Noometry Index | 48.1 | 35.5 |
| Released | 2026-01-27 | 2025-04 |
| Weights | Open | Open |
| Context window | 262K | 131K |
| Max output | 262K | 8K |
| Input $ / M tokens | $0.45 | $0.35 |
| Output $ / M tokens | $2.25 | $1.40 |
| Results tracked | 51 | 12 |
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Category by category
Coding Kimi K2.5 leads
Kimi K2.5: 48.8 (#53), Qwen3 14B: 37.3 (#195)
| Benchmark | Kimi K2.5 | Qwen3 14B |
|---|---|---|
| SciCode | 49% | 31.6% |
| SWE-bench Verified | 73.8% | — |
| SWE-bench Verified (bash only) | 70.8% | — |
| LMArena WebDev | 1437 | — |
| SWE-bench Multilingual | 67.3% | — |
| WeirdML | 45.6% | — |
| LMArena Coding | 1474 | — |
| ALE-Bench | 821.65 | — |
Agentic & Tool Use Kimi K2.5 leads
Kimi K2.5: 34.2 (#48), Qwen3 14B: 29.6 (#83)
| Benchmark | Kimi K2.5 | Qwen3 14B |
|---|---|---|
| Terminal-Bench | 43.2% | — |
| Berkeley Function Calling Leaderboard | — | 41% |
| OSWorld | 63.3% | — |
| Vending-Bench 2 | 1,198 | — |
Reasoning Kimi K2.5 leads
Kimi K2.5: 31.2 (#80), Qwen3 14B: 18.5 (#280)
| Benchmark | Kimi K2.5 | Qwen3 14B |
|---|---|---|
| Kagi LLM Benchmark | 78.5% | 49.1% |
| CritPt | 3.1% | 0% |
| Chess Puzzles | 12% | 4% |
| Epoch Capabilities Index | 148.03 | 138.23 |
| ARC-AGI-2 | 11.8% | — |
| SimpleBench | 46.8% | — |
| NYT Connections (extended) | 69.9% | — |
| ARC-AGI-1 | 65.3% | — |
| EnigmaEval | 3.4% | — |
| Thematic Generalization | 69.4% | — |
| LMArena Hard Prompts | 1453 | — |
| DTBench | — | 64% |
| LMCA | — | 18.2% |
Math Kimi K2.5 leads
Kimi K2.5: 51.8 (#53), Qwen3 14B: 38.6 (#133)
| Benchmark | Kimi K2.5 | Qwen3 14B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 92.2% | 66.4% |
| MathArena Final-Answer Competitions | 62.3% | — |
| LMArena Math | 1470 | — |
| FrontierMath (Feb 2025 set) | 27.9% | — |
| FrontierMath Tier 4 (v1) | 4.2% | — |
Knowledge Kimi K2.5 leads
Kimi K2.5: 53.6 (#56), Qwen3 14B: 39.3 (#134)
| Benchmark | Kimi K2.5 | Qwen3 14B |
|---|---|---|
| GPQA Diamond | 87.6% | 63.8% |
| Vectara Hallucination Rate | 14.2% | 5.4% |
| Humanity's Last Exam | 24.4% | — |
| SimpleQA Verified | 34.3% | — |
| LMArena Expert | 1466 | — |
Multimodal Not comparable
Kimi K2.5: 41.1 (#39), Qwen3 14B: —
| Benchmark | Kimi K2.5 | Qwen3 14B |
|---|---|---|
| LMArena Vision | 1269 | — |
| LMArena Document | 1430 | — |
Multilingual Not comparable
Kimi K2.5: 53.9 (#53), Qwen3 14B: —
| Benchmark | Kimi K2.5 | Qwen3 14B |
|---|---|---|
| LMArena Non-English | 1433 | — |
| LMArena Chinese | 1495 | — |
| LMArena French | 1454 | — |
| LMArena German | 1441 | — |
| LMArena Japanese | 1421 | — |
| LMArena Korean | 1410 | — |
| LMArena Russian | 1435 | — |
| LMArena Spanish | 1450 | — |
Instruction Following Not comparable
Kimi K2.5: 75.3 (#64), Qwen3 14B: —
| Benchmark | Kimi K2.5 | Qwen3 14B |
|---|---|---|
| LMArena Instruction Following | 1431 | — |
Long Context Kimi K2.5 leads
Kimi K2.5: 52.1 (#7), Qwen3 14B: 38.1 (#204)
| Benchmark | Kimi K2.5 | Qwen3 14B |
|---|---|---|
| Fiction.LiveBench | 86.1% | 62.5% |
| CL-bench | 19.3% | — |
| CL-bench Life | 13.2% | — |
| LMArena Longer Query | 1445 | — |
Writing & Preference Not comparable
Kimi K2.5: 65.1 (#53), Qwen3 14B: —
| Benchmark | Kimi K2.5 | Qwen3 14B |
|---|---|---|
| LMArena Text | 1445 | — |
| LMArena Creative Writing | 1423 | — |
| EQ-Bench Creative Writing | 1579 | — |
| LMArena Multi-Turn | 1444 | — |
Frequently asked questions
Is Kimi K2.5 better than Qwen3 14B?
Kimi K2.5 is the stronger model overall, scoring 48.1 to 35.5 on the Noometry Index.
Which is cheaper, Kimi K2.5 or Qwen3 14B?
Qwen3 14B is cheaper. It lists at $0.35 per million input tokens and $1.40 per million output tokens; Kimi K2.5 lists at $0.45 and $2.25.
Is Kimi K2.5 or Qwen3 14B better for coding?
Kimi K2.5 scores higher on coding benchmarks: 48.8 versus 37.3 in the Noometry coding category.
Which has the bigger context window?
Kimi K2.5 does, with 262K tokens against 131K.
How many benchmarks do Kimi K2.5 and Qwen3 14B share?
9 benchmarks have published results for both models. Kimi K2.5 has 51 scored results on Noometry and Qwen3 14B has 12.