Model comparison
GLM-4.7 vs Qwen3.5 397B (Reasoning)
Head-to-head evidence from 15 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GLM-4.7 #42 (Supported); Qwen3.5 397B (Reasoning) #56 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GLM-4.7 and Qwen3.5 397B (Reasoning) share 15 comparable benchmark results. 0 of 8 categories are comparable. 15 results are unique to GLM-4.7; 2 to Qwen3.5 397B (Reasoning).
Updated July 20, 2026- Shared results
- 15
- GLM-4.7 only
- 15
- Qwen3.5 397B (Reasoning) only
- 2
- Comparable categories
- 0 / 8
Benchmark data for GLM-4.7 and Qwen3.5 397B (Reasoning) is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 15 shared benchmark results across 5 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 has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.
Qwen3.5 397B (Reasoning) is priced at $0.60 input / $3.60 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for GLM-4.7. GLM-4.7 has the larger context window at 200K, compared with 128K for Qwen3.5 397B (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 | Qwen3.5 397B (Reasoning) |
|---|---|---|---|
| Agentic | GLM-4.745.7 | MarginNo overlap | Qwen3.5 397B (Reasoning)Not measured |
| Coding | GLM-4.775.4 | MarginNo overlap | Qwen3.5 397B (Reasoning)Not measured |
| Knowledge | GLM-4.751.8 | MarginNo overlap | Qwen3.5 397B (Reasoning)Not measured |
| Math | GLM-4.71.8 | MarginNo overlap | Qwen3.5 397B (Reasoning)Not measured |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GLM-4.7 | Qwen3.5 397B (Reasoning) | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GLM-4.7$0 input / $0 output | Qwen3.5 397B (Reasoning)$0.6 input / $3.6 output | GLM-4.7 has the lower combined listed price. |
| Generation speedtokens per second | GLM-4.782 tok/s | Qwen3.5 397B (Reasoning)Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GLM-4.71.10 s | Qwen3.5 397B (Reasoning)Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GLM-4.7200K | Qwen3.5 397B (Reasoning)128K | GLM-4.7 lists the larger context window. |
Benchmark Deep Dive
Agentic9 benchmarks
| Benchmark | GLM-4.7 | Qwen3.5 397B (Reasoning) | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 41% | — | Not comparable |
| BrowseCompSource | 52% | — | Not comparable |
| VITA-BenchSource | 15.5% | — | Not comparable |
| AA Agentic IndexSource | 25.4% | 19.9% | GLM-4.7 leads |
| τ²-bench resultsSource | 95.9% | 95.6% | GLM-4.7 leads |
| Gert LabsSource | 39.95% | — | Not comparable |
| GDPval-AASource | 33.3% | 23.1% | GLM-4.7 leads |
| GDPval-AASource | 1165 | 962 | GLM-4.7 leads |
| APEX-Agents-AASource | — | 15.3% | Not comparable |
Coding6 benchmarks
| Benchmark | GLM-4.7 | Qwen3.5 397B (Reasoning) | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 73.8% | — | Not comparable |
| LiveCodeBenchSource | 84.9% | — | Not comparable |
| SWE-RebenchSource | 58.7% | — | Not comparable |
| AA Coding IndexSource | 45.3% | 48.2% | Qwen3.5 397B (Reasoning) leads |
| AA-SciCodeSource | 45.1% | 42.0% | GLM-4.7 leads |
| AA LiveCodeBenchSource | 89.4% | — | Not comparable |
Reasoning2 benchmarks
Knowledge9 benchmarks
| Benchmark | GLM-4.7 | Qwen3.5 397B (Reasoning) | Result |
|---|---|---|---|
| GPQASource | 85.7% | — | Not comparable |
| MMLU-ProSource | 84.3% | — | Not comparable |
| HLESource | 24.8% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 33.7% | 33.7% | GLM-4.7 leads |
| AA-GPQA DiamondSource | 85.9% | 89.3% | Qwen3.5 397B (Reasoning) leads |
| AA-HLESource | 25.1% | 27.3% | Qwen3.5 397B (Reasoning) leads |
| AA-Omniscience IndexSource | -34.6% | -29.8% | Qwen3.5 397B (Reasoning) leads |
| AA-Omniscience AccuracySource | 29.3% | 31.4% | Qwen3.5 397B (Reasoning) leads |
| AA-Omniscience Hallucination RateSource | 90.3% | 89.1% | Qwen3.5 397B (Reasoning) leads |
Math3 benchmarks
Multimodal2 benchmarks
Inst. Following1 benchmarks
| Benchmark | GLM-4.7 | Qwen3.5 397B (Reasoning) | Result |
|---|---|---|---|
| AA-IFBenchSource | 67.9% | 78.8% | Qwen3.5 397B (Reasoning) leads |
Frequently Asked Questions (3)
Can I compare GLM-4.7 and Qwen3.5 397B (Reasoning) 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 GLM-4.7 and Qwen3.5 397B (Reasoning) today?
GLM-4.7: $0.00 input / $0.00 output per 1M tokens Qwen3.5 397B (Reasoning): $0.60 input / $3.60 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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