Model comparison
GLM-4.7 vs GPT-5.1-Codex-Max
Head-to-head evidence from 11 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); GPT-5.1-Codex-Max #90 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GLM-4.7 and GPT-5.1-Codex-Max share 11 comparable benchmark results. 0 of 8 categories are comparable. 19 results are unique to GLM-4.7; 2 to GPT-5.1-Codex-Max.
Updated July 20, 2026- Shared results
- 11
- GLM-4.7 only
- 19
- GPT-5.1-Codex-Max only
- 2
- Comparable categories
- 0 / 8
Benchmark data for GLM-4.7 and GPT-5.1-Codex-Max is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 11 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.
GPT-5.1-Codex-Max is priced at $1.25 input / $10.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for GLM-4.7. GPT-5.1-Codex-Max has the larger context window at 400K, compared with 200K for GLM-4.7.
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 | GPT-5.1-Codex-Max |
|---|---|---|---|
| Agentic | GLM-4.745.7 | MarginNo overlap | GPT-5.1-Codex-MaxNot measured |
| Coding | GLM-4.775.4 | MarginNo overlap | GPT-5.1-Codex-MaxNot measured |
| Knowledge | GLM-4.751.8 | MarginNo overlap | GPT-5.1-Codex-MaxNot measured |
| Math | GLM-4.71.8 | MarginNo overlap | GPT-5.1-Codex-MaxNot measured |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GLM-4.7 | GPT-5.1-Codex-Max | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GLM-4.7$0 input / $0 output | GPT-5.1-Codex-Max$1.25 input / $10 output | GLM-4.7 has the lower combined listed price. |
| Generation speedtokens per second | GLM-4.782 tok/s | GPT-5.1-Codex-MaxNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GLM-4.71.10 s | GPT-5.1-Codex-MaxNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GLM-4.7200K | GPT-5.1-Codex-Max400K | GPT-5.1-Codex-Max lists the larger context window. |
Benchmark Deep Dive
Agentic8 benchmarks
| Benchmark | GLM-4.7 | GPT-5.1-Codex-Max | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 41% | — | Not comparable |
| BrowseCompSource | 52% | — | Not comparable |
| VITA-BenchSource | 15.5% | — | Not comparable |
| AA Agentic IndexSource | 25.4% | — | Not comparable |
| τ²-bench resultsSource | 95.9% | 83% | GLM-4.7 leads |
| Gert LabsSource | 39.95% | — | Not comparable |
| GDPval-AASource | 33.3% | — | Not comparable |
| GDPval-AASource | 1165 | — | Not comparable |
Coding7 benchmarks
| Benchmark | GLM-4.7 | GPT-5.1-Codex-Max | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 73.8% | — | Not comparable |
| LiveCodeBenchSource | 84.9% | — | Not comparable |
| SWE-RebenchSource | 58.7% | — | Not comparable |
| AA Coding IndexSource | 45.3% | — | Not comparable |
| AA-SciCodeSource | 45.1% | 40.2% | GLM-4.7 leads |
| AA LiveCodeBenchSource | 89.4% | — | Not comparable |
| Vibe Code BenchSource | — | 22.17% | Not comparable |
Reasoning2 benchmarks
Knowledge9 benchmarks
| Benchmark | GLM-4.7 | GPT-5.1-Codex-Max | Result |
|---|---|---|---|
| GPQASource | 85.7% | — | Not comparable |
| MMLU-ProSource | 84.3% | — | Not comparable |
| HLESource | 24.8% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 33.7% | 34.7% | GPT-5.1-Codex-Max leads |
| AA-GPQA DiamondSource | 85.9% | 86.0% | GPT-5.1-Codex-Max leads |
| AA-HLESource | 25.1% | 23.4% | GLM-4.7 leads |
| AA-Omniscience IndexSource | -34.6% | -6.0% | GPT-5.1-Codex-Max leads |
| AA-Omniscience AccuracySource | 29.3% | 39.2% | GPT-5.1-Codex-Max leads |
| AA-Omniscience Hallucination RateSource | 90.3% | 74.4% | GPT-5.1-Codex-Max leads |
Math3 benchmarks
Multimodal2 benchmarks
Inst. Following1 benchmarks
| Benchmark | GLM-4.7 | GPT-5.1-Codex-Max | Result |
|---|---|---|---|
| AA-IFBenchSource | 67.9% | 70.0% | GPT-5.1-Codex-Max leads |
Frequently Asked Questions (3)
Can I compare GLM-4.7 and GPT-5.1-Codex-Max 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 GPT-5.1-Codex-Max today?
GLM-4.7: $0.00 input / $0.00 output per 1M tokens GPT-5.1-Codex-Max: $1.25 input / $10.00 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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