Model comparison
Kimi K2.5 (Reasoning) vs Qwen2.5-VL-32B
Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Kimi K2.5 (Reasoning) #57 (Estimated); Qwen2.5-VL-32B #175 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Kimi K2.5 (Reasoning) and Qwen2.5-VL-32B share 0 comparable benchmark results. 0 of 8 categories are comparable. 27 results are unique to Kimi K2.5 (Reasoning); 0 to Qwen2.5-VL-32B.
Updated July 21, 2026- Shared results
- 0
- Kimi K2.5 (Reasoning) only
- 27
- Qwen2.5-VL-32B only
- 0
- Comparable categories
- 0 / 8
Benchmark data for Kimi K2.5 (Reasoning) and Qwen2.5-VL-32B is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
BenchLM does not have sourced benchmark coverage for Qwen2.5-VL-32B yet. This comparison is currently limited to metadata such as context window, reasoning mode, and pricing where available.
Kimi K2.5 (Reasoning) is priced at $0.60 input / $3.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Qwen2.5-VL-32B. Kimi K2.5 (Reasoning) has the larger context window at 128K, compared with 32K for Qwen2.5-VL-32B.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Kimi K2.5 (Reasoning) | Qwen2.5-VL-32B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Kimi K2.5 (Reasoning)$0.6 input / $3 output | Qwen2.5-VL-32B$0 input / $0 output | Qwen2.5-VL-32B has the lower combined listed price. |
| Generation speedtokens per second | Kimi K2.5 (Reasoning)Not available | Qwen2.5-VL-32BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Kimi K2.5 (Reasoning)Not available | Qwen2.5-VL-32BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Kimi K2.5 (Reasoning)128K | Qwen2.5-VL-32B32K | Kimi K2.5 (Reasoning) lists the larger context window. |
Benchmark Deep Dive
Agentic8 benchmarks
| Benchmark | Kimi K2.5 (Reasoning) | Qwen2.5-VL-32B | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 50.8% | — | Not comparable |
| BrowseCompSource | 60.6% | — | Not comparable |
| APEX-Agents-AASource | 11.5% | — | Not comparable |
| τ²-bench resultsSource | 95.9% | — | Not comparable |
| Gert LabsSource | 32.58% | — | Not comparable |
| AA Agentic IndexSource | 21.7% | — | Not comparable |
| GDPval-AASource | 25.4% | — | Not comparable |
| GDPval-AASource | 1009 | — | Not comparable |
Coding4 benchmarks
Reasoning2 benchmarks
Knowledge8 benchmarks
| Benchmark | Kimi K2.5 (Reasoning) | Qwen2.5-VL-32B | Result |
|---|---|---|---|
| GPQASource | 87.6% | — | Not comparable |
| MMLU-ProSource | 87.1% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 35.4% | — | Not comparable |
| AA-GPQA DiamondSource | 87.9% | — | Not comparable |
| AA-HLESource | 29.4% | — | Not comparable |
| AA-Omniscience IndexSource | -8.1% | — | Not comparable |
| AA-Omniscience AccuracySource | 34.3% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 64.6% | — | Not comparable |
Math1 benchmarks
| Benchmark | Kimi K2.5 (Reasoning) | Qwen2.5-VL-32B | Result |
|---|---|---|---|
| AIME 2025Source | 96.1% | — | Not comparable |
Multimodal3 benchmarks
Inst. Following1 benchmarks
| Benchmark | Kimi K2.5 (Reasoning) | Qwen2.5-VL-32B | Result |
|---|---|---|---|
| AA-IFBenchSource | 70.2% | — | Not comparable |
Frequently Asked Questions (3)
Can I compare Kimi K2.5 (Reasoning) and Qwen2.5-VL-32B on BenchLM yet?
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
Why does this comparison show “coming soon”?
BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.
What data is available for Kimi K2.5 (Reasoning) and Qwen2.5-VL-32B today?
Kimi K2.5 (Reasoning): $0.60 input / $3.00 output per 1M tokens Qwen2.5-VL-32B: $0.00 input / $0.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
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