Model comparison
Kimi K2 (Jul 2025) vs Phi-4 Mini
Kimi K2 (Jul 2025) is the stronger model overall, scoring 41.2 to 30.9 on the Noometry Index. Phi-4 Mini costs 7.6× less per token, which makes it the better buy when Kimi K2 (Jul 2025)'s lead doesn't matter for your workload.
Last verified . 1 shared benchmarks.
MicrosoftSummary
- They share 1 benchmark with published results for both. Kimi K2 (Jul 2025) scores higher in 3 categories and Phi-4 Mini in 0 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in coding, where Kimi K2 (Jul 2025) leads 42.4 to 28.1.
- The biggest single-benchmark swing is Vectara Hallucination Rate: 17.9% for Kimi K2 (Jul 2025) and 23.5% for Phi-4 Mini.
- Phi-4 Mini is cheaper at $0.075 / $0.30 per million input/output tokens, against $0.57 / $2.30 for Kimi K2 (Jul 2025).
- Kimi K2 (Jul 2025) accepts more context: 262K tokens versus 128K.
Side by side
| Kimi K2 (Jul 2025) | Phi-4 Mini | |
|---|---|---|
| Provider | Moonshot AI | Microsoft |
| Noometry Index | 41.2 | 30.9 |
| Released | 2025-07-12 | 2024-12-11 |
| Weights | Open | Open |
| Context window | 262K | 128K |
| Max output | 262K | 4K |
| Input $ / M tokens | $0.57 | $0.075 |
| Output $ / M tokens | $2.30 | $0.30 |
| Results tracked | 42 | 3 |
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Category by category
Coding Kimi K2 (Jul 2025) leads
Kimi K2 (Jul 2025): 42.4 (#102), Phi-4 Mini: 28.1 (#317)
| Benchmark | Kimi K2 (Jul 2025) | Phi-4 Mini |
|---|---|---|
| SWE-bench Verified (bash only) | 63.4% | — |
| Aider Polyglot | 59.1% | — |
| SciCode | — | 10.8% |
| GSO | 4.9% | — |
| WeirdML | 42.8% | — |
| LMArena Coding | 1399 | — |
| ALE-Bench | 597.5 | — |
Agentic & Tool Use Not comparable
Kimi K2 (Jul 2025): 32.4 (#64), Phi-4 Mini: —
| Benchmark | Kimi K2 (Jul 2025) | Phi-4 Mini |
|---|---|---|
| Terminal-Bench | 35.7% | — |
| Berkeley Function Calling Leaderboard | 59.1% | — |
| METR Time Horizons | 59.2% | — |
Reasoning Too close to call
Kimi K2 (Jul 2025): 23.3 (#179), Phi-4 Mini: 22.4 (#195)
| Benchmark | Kimi K2 (Jul 2025) | Phi-4 Mini |
|---|---|---|
| SimpleBench | 26.3% | — |
| Kagi LLM Benchmark | 64.4% | — |
| CritPt | — | 0% |
| LMArena Hard Prompts | 1384 | — |
| Epoch Capabilities Index | 146.01 | — |
| ForecastBench | 60.2 | — |
Math Not comparable
Kimi K2 (Jul 2025): 42.7 (#83), Phi-4 Mini: —
| Benchmark | Kimi K2 (Jul 2025) | Phi-4 Mini |
|---|---|---|
| Omni-MATH | 65.4% | — |
| LMArena Math | 1397 | — |
| FrontierMath (Feb 2025 set) | 21.4% | — |
| FrontierMath Tier 4 (v1) | 0% | — |
Knowledge Kimi K2 (Jul 2025) leads
Kimi K2 (Jul 2025): 37.3 (#157), Phi-4 Mini: 25.3 (#262)
| Benchmark | Kimi K2 (Jul 2025) | Phi-4 Mini |
|---|---|---|
| Vectara Hallucination Rate | 17.9% | 23.5% |
| MMLU-Pro | 81.9% | — |
| Confabulations | 20.4% | — |
| GPQA (HELM) | 65.3% | — |
| LMArena Expert | 1365 | — |
Multilingual Not comparable
Kimi K2 (Jul 2025): 49.6 (#130), Phi-4 Mini: —
| Benchmark | Kimi K2 (Jul 2025) | Phi-4 Mini |
|---|---|---|
| LMArena Non-English | 1372 | — |
| LMArena Chinese | 1415 | — |
| LMArena French | 1379 | — |
| LMArena German | 1387 | — |
| LMArena Japanese | 1349 | — |
| LMArena Korean | 1325 | — |
| LMArena Russian | 1385 | — |
| LMArena Spanish | 1386 | — |
Instruction Following Not comparable
Kimi K2 (Jul 2025): 71.1 (#156), Phi-4 Mini: —
| Benchmark | Kimi K2 (Jul 2025) | Phi-4 Mini |
|---|---|---|
| IFEval | 85% | — |
| LMArena Instruction Following | 1348 | — |
Long Context Not comparable
Kimi K2 (Jul 2025): 41.2 (#145), Phi-4 Mini: —
| Benchmark | Kimi K2 (Jul 2025) | Phi-4 Mini |
|---|---|---|
| Fiction.LiveBench | 66.7% | — |
| CL-bench | 17.6% | — |
| LMArena Longer Query | 1353 | — |
Writing & Preference Not comparable
Kimi K2 (Jul 2025): 62.3 (#78), Phi-4 Mini: —
| Benchmark | Kimi K2 (Jul 2025) | Phi-4 Mini |
|---|---|---|
| LMArena Text | 1380 | — |
| LMArena Creative Writing | 1350 | — |
| Short-Story Creative Writing | 85.6% | — |
| EQ-Bench Creative Writing | 1666 | — |
| WildBench | 86.2% | — |
| LMArena Multi-Turn | 1371 | — |
Frequently asked questions
Is Kimi K2 (Jul 2025) better than Phi-4 Mini?
Kimi K2 (Jul 2025) is the stronger model overall, scoring 41.2 to 30.9 on the Noometry Index. Phi-4 Mini costs 7.6× less per token, which makes it the better buy when Kimi K2 (Jul 2025)'s lead doesn't matter for your workload.
Which is cheaper, Kimi K2 (Jul 2025) or Phi-4 Mini?
Phi-4 Mini is cheaper. It lists at $0.075 per million input tokens and $0.30 per million output tokens; Kimi K2 (Jul 2025) lists at $0.57 and $2.30.
Is Kimi K2 (Jul 2025) or Phi-4 Mini better for coding?
Kimi K2 (Jul 2025) scores higher on coding benchmarks: 42.4 versus 28.1 in the Noometry coding category.
Which has the bigger context window?
Kimi K2 (Jul 2025) does, with 262K tokens against 128K.
How many benchmarks do Kimi K2 (Jul 2025) and Phi-4 Mini share?
1 benchmark has published results for both models. Kimi K2 (Jul 2025) has 42 scored results on Noometry and Phi-4 Mini has 3.