Model comparison
GLM-4.7 vs Kimi K2.5 (Reasoning)
Head-to-head evidence from 23 shared benchmark results across 7 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GLM-4.7 #42 (Supported); Kimi K2.5 (Reasoning) #57 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GLM-4.7 and Kimi K2.5 (Reasoning) share 23 comparable benchmark results. 3 of 8 categories are comparable. 7 results are unique to GLM-4.7; 4 to Kimi K2.5 (Reasoning).
Updated July 22, 2026- Shared results
- 23
- GLM-4.7 only
- 7
- Kimi K2.5 (Reasoning) only
- 4
- Comparable categories
- 3 / 8
Pick GLM-4.7 if you want the stronger benchmark profile. Kimi K2.5 (Reasoning) only becomes the better choice if knowledge is the priority.
Confidence note. This is a partial-evidence comparison with 23 shared benchmark results across 7 evidence categories; 3 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
GLM-4.7 has the cleaner BenchAlign overall profile here, landing at 61.16 versus 59.35. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
Kimi K2.5 (Reasoning) is also the more expensive model on tokens at $0.60 input / $3.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for GLM-4.7. That is roughly Infinityx on output cost alone. GLM-4.7 gives you the larger context window at 200K, compared with 128K for Kimi K2.5 (Reasoning).
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | GLM-4.7 | Δ | Kimi K2.5 (Reasoning) |
|---|---|---|---|
| Knowledge | GLM-4.751.8 | Margin→ 35.4 | Kimi K2.5 (Reasoning)87.2 |
| Agentic | GLM-4.745.7 | Margin→ 9.3 | Kimi K2.5 (Reasoning)55.0 |
| Coding | GLM-4.775.4 | Margin→ 1.4 | Kimi K2.5 (Reasoning)76.8 |
| Math | GLM-4.71.8 | MarginNo overlap | Kimi K2.5 (Reasoning)Not measured |
| Multimodal | GLM-4.7Not measured | MarginNo overlap | Kimi K2.5 (Reasoning)78.5 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
Terminal-Bench 2.0
AgenticA 41%B 50.8%Winner: Kimi K2.5 (Reasoning)Δ 9.8Terminal-Bench 2.0: GLM-4.7 scored 41%; Kimi K2.5 (Reasoning) scored 50.8%. Kimi K2.5 (Reasoning) wins this benchmark. - Source ↗
BrowseComp
AgenticA 52%B 60.6%Winner: Kimi K2.5 (Reasoning)Δ 8.6BrowseComp: GLM-4.7 scored 52%; Kimi K2.5 (Reasoning) scored 60.6%. Kimi K2.5 (Reasoning) wins this benchmark. - Source ↗
SWE-bench Verified
CodingA 73.8%B 76.8%Winner: Kimi K2.5 (Reasoning)Δ 3SWE-bench Verified: GLM-4.7 scored 73.8%; Kimi K2.5 (Reasoning) scored 76.8%. Kimi K2.5 (Reasoning) wins this benchmark. - Source ↗
MMLU-Pro
KnowledgeA 84.3%B 87.1%Winner: Kimi K2.5 (Reasoning)Δ 2.8MMLU-Pro: GLM-4.7 scored 84.3%; Kimi K2.5 (Reasoning) scored 87.1%. Kimi K2.5 (Reasoning) wins this benchmark. - Source ↗
GPQA
KnowledgeA 85.7%B 87.6%Winner: Kimi K2.5 (Reasoning)Δ 1.9GPQA: GLM-4.7 scored 85.7%; Kimi K2.5 (Reasoning) scored 87.6%. Kimi K2.5 (Reasoning) wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GLM-4.7 | Kimi K2.5 (Reasoning) | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GLM-4.7$0 input / $0 output | Kimi K2.5 (Reasoning)$0.6 input / $3 output | GLM-4.7 has the lower combined listed price. |
| Generation speedtokens per second | GLM-4.782 tok/s | Kimi K2.5 (Reasoning)Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GLM-4.71.10 s | Kimi K2.5 (Reasoning)Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GLM-4.7200K | Kimi K2.5 (Reasoning)128K | GLM-4.7 lists the larger context window. |
Benchmark Deep Dive
AgenticKimi K2.5 (Reasoning) wins9 benchmarks
| Benchmark | GLM-4.7 | Kimi K2.5 (Reasoning) | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 41% | 50.8% | Kimi K2.5 (Reasoning) leads |
| BrowseCompSource | 52% | 60.6% | Kimi K2.5 (Reasoning) leads |
| VITA-BenchSource | 15.5% | — | Not comparable |
| AA Agentic IndexSource | 25.4% | 21.7% | GLM-4.7 leads |
| τ²-bench resultsSource | 95.9% | 95.9% | Tie |
| Gert LabsSource | 39.95% | 32.58% | GLM-4.7 leads |
| GDPval-AASource | 33.3% | 25.4% | GLM-4.7 leads |
| GDPval-AASource | 1165 | 1009 | GLM-4.7 leads |
| APEX-Agents-AASource | — | 11.5% | Not comparable |
CodingKimi K2.5 (Reasoning) wins7 benchmarks
| Benchmark | GLM-4.7 | Kimi K2.5 (Reasoning) | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 73.8% | 76.8% | Kimi K2.5 (Reasoning) leads |
| LiveCodeBenchSource | 84.9% | — | Not comparable |
| SWE-RebenchSource | 58.7% | — | Not comparable |
| AA Coding IndexSource | 45.3% | 46.8% | Kimi K2.5 (Reasoning) leads |
| AA-SciCodeSource | 45.1% | 49.0% | Kimi K2.5 (Reasoning) leads |
| AA LiveCodeBenchSource | 89.4% | — | Not comparable |
| Vibe Code BenchSource | — | 17.54% | Not comparable |
Reasoning2 benchmarks
KnowledgeKimi K2.5 (Reasoning) wins9 benchmarks
| Benchmark | GLM-4.7 | Kimi K2.5 (Reasoning) | Result |
|---|---|---|---|
| GPQASource | 85.7% | 87.6% | Kimi K2.5 (Reasoning) leads |
| MMLU-ProSource | 84.3% | 87.1% | Kimi K2.5 (Reasoning) leads |
| HLESource | 24.8% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 33.7% | 35.4% | Kimi K2.5 (Reasoning) leads |
| AA-GPQA DiamondSource | 85.9% | 87.9% | Kimi K2.5 (Reasoning) leads |
| AA-HLESource | 25.1% | 29.4% | Kimi K2.5 (Reasoning) leads |
| AA-Omniscience IndexSource | -34.6% | -8.1% | Kimi K2.5 (Reasoning) leads |
| AA-Omniscience AccuracySource | 29.3% | 34.3% | Kimi K2.5 (Reasoning) leads |
| AA-Omniscience Hallucination RateSource | 90.3% | 64.6% | Kimi K2.5 (Reasoning) leads |
Math3 benchmarks
Multimodal3 benchmarks
Inst. Following1 benchmarks
| Benchmark | GLM-4.7 | Kimi K2.5 (Reasoning) | Result |
|---|---|---|---|
| AA-IFBenchSource | 67.9% | 70.2% | Kimi K2.5 (Reasoning) leads |
Frequently Asked Questions (4)
Which is better, GLM-4.7 or Kimi K2.5 (Reasoning)?
GLM-4.7 is ahead on BenchLM's BenchAlign leaderboard, 61.16 to 59.35. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 41% and 50.8%.
Which is better for knowledge tasks, GLM-4.7 or Kimi K2.5 (Reasoning)?
Kimi K2.5 (Reasoning) has the edge for knowledge tasks in this comparison, averaging 87.2 versus 51.8. Inside this category, AA-Omniscience Index is the benchmark that creates the most daylight between them.
Which is better for coding, GLM-4.7 or Kimi K2.5 (Reasoning)?
Kimi K2.5 (Reasoning) has the edge for coding in this comparison, averaging 76.8 versus 75.4. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, GLM-4.7 or Kimi K2.5 (Reasoning)?
Kimi K2.5 (Reasoning) has the edge for agentic tasks in this comparison, averaging 55 versus 45.7. Inside this category, GDPval-AA is the benchmark that creates the most daylight between them.
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