Model comparison
GLM-4.7 vs o3-mini
Head-to-head evidence from 7 shared benchmark results across 3 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GLM-4.7 #42 (Supported); o3-mini #136 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GLM-4.7 and o3-mini share 7 comparable benchmark results. 2 of 8 categories are comparable. 23 results are unique to GLM-4.7; 3 to o3-mini.
Updated July 24, 2026- Shared results
- 7
- GLM-4.7 only
- 23
- o3-mini only
- 3
- Comparable categories
- 2 / 8
Pick GLM-4.7 if you want the stronger benchmark profile. o3-mini only becomes the better choice if knowledge is the priority.
Confidence note. This is a partial-evidence comparison with 7 shared benchmark results across 3 evidence categories; 2 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 is clearly ahead on the BenchAlign aggregate, 61.16 to 47.41. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GLM-4.7's sharpest advantage is in coding, where it averages 75.4 against 49.3. The single biggest benchmark swing on the page is SWE-bench Verified, 73.8% to 49.3%. o3-mini does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
o3-mini is also the more expensive model on tokens at $1.10 input / $4.40 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.
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 | o3-mini |
|---|---|---|---|
| Coding | GLM-4.775.4 | Margin← 26.1 | o3-mini49.3 |
| Knowledge | GLM-4.751.8 | Margin→ 25.4 | o3-mini77.2 |
| Agentic | GLM-4.745.7 | MarginNo overlap | o3-miniNot measured |
| Math | GLM-4.71.8 | MarginNo overlap | o3-miniNot measured |
| Inst. Following | GLM-4.7Not measured | MarginNo overlap | o3-mini93.9 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GLM-4.7 | o3-mini | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GLM-4.7$0 input / $0 output | o3-mini$1.1 input / $4.4 output | GLM-4.7 has the lower combined listed price. |
| Generation speedtokens per second | GLM-4.782 tok/s | o3-mini160 tok/s | o3-mini has the higher measured throughput. |
| First-answer latencyseconds to first token | GLM-4.71.10 s | o3-mini7.12 s | GLM-4.7 reaches the first token sooner. |
| Context windowmaximum listed tokens | GLM-4.7200K | o3-mini200K | Listed context windows are equal. |
Benchmark Deep Dive
Agentic8 benchmarks
| Benchmark | GLM-4.7 | o3-mini | 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% | 28.7% | GLM-4.7 leads |
| Gert LabsSource | 39.95% | — | Not comparable |
| GDPval-AASource | 33.3% | — | Not comparable |
| GDPval-AASource | 1165 | — | Not comparable |
CodingGLM-4.7 wins6 benchmarks
Reasoning2 benchmarks
Knowledgeo3-mini wins10 benchmarks
| Benchmark | GLM-4.7 | o3-mini | Result |
|---|---|---|---|
| GPQASource | 85.7% | 77.2% | GLM-4.7 leads |
| MMLU-ProSource | 84.3% | — | Not comparable |
| HLESource | 24.8% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 33.7% | 19.0% | GLM-4.7 leads |
| AA-GPQA DiamondSource | 85.9% | 74.8% | GLM-4.7 leads |
| AA-HLESource | 25.1% | 8.7% | GLM-4.7 leads |
| AA-Omniscience IndexSource | -34.6% | — | Not comparable |
| AA-Omniscience AccuracySource | 29.3% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 90.3% | — | Not comparable |
| MMLUSource | — | 86.9% | Not comparable |
Math4 benchmarks
Multimodal1 benchmarks
| Benchmark | GLM-4.7 | o3-mini | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1255 | — | Not comparable |
Frequently Asked Questions (3)
Which is better, GLM-4.7 or o3-mini?
GLM-4.7 is ahead on BenchLM's BenchAlign leaderboard, 61.16 to 47.41. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 73.8% and 49.3%.
Which is better for knowledge tasks, GLM-4.7 or o3-mini?
o3-mini has the edge for knowledge tasks in this comparison, averaging 77.2 versus 51.8. Inside this category, AA-HLE is the benchmark that creates the most daylight between them.
Which is better for coding, GLM-4.7 or o3-mini?
GLM-4.7 has the edge for coding in this comparison, averaging 75.4 versus 49.3. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
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