Model comparison
Claude Sonnet 4.6 vs GLM-4.7-Flash
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: Claude Sonnet 4.6 #32 (Supported); GLM-4.7-Flash #106 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude Sonnet 4.6 and GLM-4.7-Flash share 0 comparable benchmark results. 0 of 8 categories are comparable. 33 results are unique to Claude Sonnet 4.6; 0 to GLM-4.7-Flash.
Updated July 21, 2026- Shared results
- 0
- Claude Sonnet 4.6 only
- 33
- GLM-4.7-Flash only
- 0
- Comparable categories
- 0 / 8
Benchmark data for Claude Sonnet 4.6 and GLM-4.7-Flash 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 GLM-4.7-Flash yet. This comparison is currently limited to metadata such as context window, reasoning mode, and pricing where available.
Claude Sonnet 4.6 is priced at $3.00 input / $15.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for GLM-4.7-Flash.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude Sonnet 4.6 | GLM-4.7-Flash | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude Sonnet 4.6$3 input / $15 output | GLM-4.7-Flash$0 input / $0 output | GLM-4.7-Flash has the lower combined listed price. |
| Generation speedtokens per second | Claude Sonnet 4.644 tok/s | GLM-4.7-Flash95 tok/s | GLM-4.7-Flash has the higher measured throughput. |
| First-answer latencyseconds to first token | Claude Sonnet 4.61.48 s | GLM-4.7-Flash0.91 s | GLM-4.7-Flash reaches the first token sooner. |
| Context windowmaximum listed tokens | Claude Sonnet 4.6200K | GLM-4.7-Flash200K | Listed context windows are equal. |
Benchmark Deep Dive
Agentic8 benchmarks
| Benchmark | Claude Sonnet 4.6 | GLM-4.7-Flash | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 59.1% | — | Not comparable |
| OSWorld-VerifiedSource | 72.1% | — | Not comparable |
| Claw-EvalSource | 67.8% | — | Not comparable |
| CyberGymSource | 65.2% | — | Not comparable |
| τ²-bench resultsSource | 79.5% | — | Not comparable |
| Gert LabsSource | 62.92% | — | Not comparable |
| OSWorld 2.0Source | 8.3% | — | Not comparable |
| JobBenchSource | 36.9% | — | Not comparable |
Coding7 benchmarks
| Benchmark | Claude Sonnet 4.6 | GLM-4.7-Flash | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 79.6% | — | Not comparable |
| SWE-RebenchSource | 60.7% | — | Not comparable |
| React Native EvalsSource | 80.6% | — | Not comparable |
| Vibe Code BenchSource | 51.48% | — | Not comparable |
| cursorBench31Source | 48.8% | — | Not comparable |
| AA-SciCodeSource | 46.9% | — | Not comparable |
| FrontierCode 1.1 MainSource | 24.3% | — | Not comparable |
Reasoning2 benchmarks
Knowledge10 benchmarks
| Benchmark | Claude Sonnet 4.6 | GLM-4.7-Flash | Result |
|---|---|---|---|
| GPQASource | 89.9% | — | Not comparable |
| SuperGPQASource | 95% | — | Not comparable |
| MMLU-ProSource | 79.2% | — | Not comparable |
| HLESource | 49% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 35.9% | — | Not comparable |
| AA-GPQA DiamondSource | 79.9% | — | Not comparable |
| AA-HLESource | 13.2% | — | Not comparable |
| AA-Omniscience IndexSource | -2.9% | — | Not comparable |
| AA-Omniscience AccuracySource | 38.0% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 65.9% | — | Not comparable |
Math2 benchmarks
Multimodal3 benchmarks
Inst. Following1 benchmarks
| Benchmark | Claude Sonnet 4.6 | GLM-4.7-Flash | Result |
|---|---|---|---|
| AA-IFBenchSource | 41.2% | — | Not comparable |
Frequently Asked Questions (3)
Can I compare Claude Sonnet 4.6 and GLM-4.7-Flash 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 Claude Sonnet 4.6 and GLM-4.7-Flash today?
Claude Sonnet 4.6: $3.00 input / $15.00 output per 1M tokens GLM-4.7-Flash: $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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