Model comparison
Claude Opus 4.6 vs GLM-4.5
Head-to-head evidence from 1 shared benchmark result across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Claude Opus 4.6 #16 (Supported); GLM-4.5 #68 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude Opus 4.6 and GLM-4.5 share 1 comparable benchmark result. 0 of 8 categories are comparable. 45 results are unique to Claude Opus 4.6; 0 to GLM-4.5.
Updated July 20, 2026- Shared results
- 1
- Claude Opus 4.6 only
- 45
- GLM-4.5 only
- 0
- Comparable categories
- 0 / 8
Benchmark data for Claude Opus 4.6 and GLM-4.5 is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 1 shared benchmark result across 1 evidence category; 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.
Claude Opus 4.6 is priced at $5.00 input / $25.00 output per 1M tokens, versus $0.60 input / $2.20 output per 1M tokens for GLM-4.5. Claude Opus 4.6 has the larger context window at 1M, compared with 128K for GLM-4.5.
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 | Claude Opus 4.6 | Δ | GLM-4.5 |
|---|---|---|---|
| Agentic | Claude Opus 4.673.0 | MarginNo overlap | GLM-4.5Not measured |
| Coding | Claude Opus 4.668.1 | MarginNo overlap | GLM-4.5Not measured |
| Knowledge | Claude Opus 4.669.1 | MarginNo overlap | GLM-4.5Not measured |
| Math | Claude Opus 4.636.3 | MarginNo overlap | GLM-4.5Not measured |
| Multimodal | Claude Opus 4.677.3 | MarginNo overlap | GLM-4.5Not measured |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude Opus 4.6 | GLM-4.5 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude Opus 4.6$5 input / $25 output | GLM-4.5$0.6 input / $2.2 output | GLM-4.5 has the lower combined listed price. |
| Generation speedtokens per second | Claude Opus 4.640 tok/s | GLM-4.551 tok/s | GLM-4.5 has the higher measured throughput. |
| First-answer latencyseconds to first token | Claude Opus 4.61.78 s | GLM-4.51.45 s | GLM-4.5 reaches the first token sooner. |
| Context windowmaximum listed tokens | Claude Opus 4.61M | GLM-4.5128K | Claude Opus 4.6 lists the larger context window. |
Benchmark Deep Dive
Agentic10 benchmarks
| Benchmark | Claude Opus 4.6 | GLM-4.5 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 65.4% | — | Not comparable |
| BrowseCompSource | 83.7% | — | Not comparable |
| OSWorld-VerifiedSource | 72.7% | — | Not comparable |
| τ²-bench resultsSource | 84.8% | — | Not comparable |
| Claw-EvalSource | 70.4% | — | Not comparable |
| DeepSearchQASource | 73.7% | — | Not comparable |
| CyberGymSource | 66.6% | — | Not comparable |
| Gert LabsSource | 61.85% | — | Not comparable |
| ResearchClawBenchSource | 19.9% | — | Not comparable |
| JobBenchSource | 36.7% | — | Not comparable |
Coding9 benchmarks
| Benchmark | Claude Opus 4.6 | GLM-4.5 | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 80.8% | — | Not comparable |
| SWE-bench Verified*Source | 75.6% | — | Not comparable |
| LiveCodeBench ProSource | 70.7% | — | Not comparable |
| SWE-bench ProSource | 53.4% | — | Not comparable |
| SWE-RebenchSource | 65.3% | — | Not comparable |
| React Native EvalsSource | 84.1% | — | Not comparable |
| Vibe Code BenchSource | 57.57% | — | Not comparable |
| AA-SciCodeSource | 45.7% | — | Not comparable |
| FrontierCode 1.1 MainSource | 26.9% | — | Not comparable |
Reasoning2 benchmarks
Knowledge15 benchmarks
| Benchmark | Claude Opus 4.6 | GLM-4.5 | Result |
|---|---|---|---|
| GPQASource | 91.3% | — | Not comparable |
| GPQA-DSource | 89.2% | — | Not comparable |
| SuperGPQASource | 95% | — | Not comparable |
| MMLU-ProSource | 82% | — | Not comparable |
| MMLU-Pro (Arcee)Source | 89.1% | — | Not comparable |
| HLESource | 53% | — | Not comparable |
| HLE w/o toolsSource | 40% | — | Not comparable |
| HealthBench HardSource | 14.8% | — | Not comparable |
| MedXpertQA (Text)Source | 52.1% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 37.8% | — | Not comparable |
| AA-GPQA DiamondSource | 84.0% | — | Not comparable |
| AA-HLESource | 18.6% | — | Not comparable |
| AA-Omniscience IndexSource | 3.5% | — | Not comparable |
| AA-Omniscience AccuracySource | 45.2% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 76.0% | — | Not comparable |
Math3 benchmarks
Multimodal6 benchmarks
Inst. Following1 benchmarks
| Benchmark | Claude Opus 4.6 | GLM-4.5 | Result |
|---|---|---|---|
| AA-IFBenchSource | 44.6% | — | Not comparable |
Frequently Asked Questions (3)
Can I compare Claude Opus 4.6 and GLM-4.5 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 Opus 4.6 and GLM-4.5 today?
Claude Opus 4.6: $5.00 input / $25.00 output per 1M tokens GLM-4.5: $0.60 input / $2.20 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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