Model comparison
GLM-4.7 vs Step 3.7 Flash
Head-to-head evidence from 20 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Verified leaderboard positions: GLM-4.7 #32; Step 3.7 Flash unranked
BenchAlign evidence: GLM-4.7 supported; Step 3.7 Flash estimated. Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GLM-4.7 and Step 3.7 Flash share 20 comparable benchmark results. 2 of 8 categories are comparable. 11 results are unique to GLM-4.7; 10 to Step 3.7 Flash.
Updated July 16, 2026- Shared results
- 20
- GLM-4.7 only
- 11
- Step 3.7 Flash only
- 10
- Comparable categories
- 2 / 8
Pick GLM-4.7 if you want the stronger benchmark profile. Step 3.7 Flash only becomes the better choice if agentic is the priority or you need the larger 256K context window.
Confidence note. This is a partial-evidence comparison with 20 shared benchmark results across 6 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 provisional aggregate, 62 to 57. 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 56.3. The single biggest benchmark swing on the page is BrowseComp, 52% to 75.8%. Step 3.7 Flash does hit back in agentic, so the answer changes if that is the part of the workload you care about most.
Step 3.7 Flash is also the more expensive model on tokens at $0.20 input / $1.15 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. Step 3.7 Flash gives you the larger context window at 256K, 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 | Step 3.7 Flash |
|---|---|---|---|
| Agentic | GLM-4.745.7 | Margin→ 20.7 | Step 3.7 Flash66.4 |
| Coding | GLM-4.775.4 | Margin← 19.1 | Step 3.7 Flash56.3 |
| Knowledge | GLM-4.752.1 | MarginNo overlap | Step 3.7 FlashNot measured |
| Math | GLM-4.71.8 | MarginNo overlap | Step 3.7 FlashNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
BrowseComp
AgenticA 52%B 75.8%Winner: Step 3.7 FlashΔ 23.8BrowseComp: GLM-4.7 scored 52%; Step 3.7 Flash scored 75.8%. Step 3.7 Flash wins this benchmark. - Source ↗
Terminal-Bench 2.0
AgenticA 41%B 59.5%Winner: Step 3.7 FlashΔ 18.5Terminal-Bench 2.0: GLM-4.7 scored 41%; Step 3.7 Flash scored 59.5%. Step 3.7 Flash wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GLM-4.7 | Step 3.7 Flash | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GLM-4.7$0 input / $0 output | Step 3.7 Flash$0.2 input / $1.15 output | GLM-4.7 has the lower combined listed price. |
| Generation speedtokens per second | GLM-4.782 tok/s | Step 3.7 FlashNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GLM-4.71.10 s | Step 3.7 FlashNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GLM-4.7200K | Step 3.7 Flash256K | Step 3.7 Flash lists the larger context window. |
Benchmark Deep Dive
AgenticStep 3.7 Flash wins13 benchmarks
| Benchmark | GLM-4.7 | Step 3.7 Flash | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 41% | 59.5% | Step 3.7 Flash leads |
| BrowseCompSource | 52% | 75.8% | Step 3.7 Flash leads |
| VITA-BenchSource | 15.5% | — | Not comparable |
| AA Agentic IndexSource | 25.4% | 21.5% | GLM-4.7 leads |
| τ²-bench resultsSource | 95.9% | 98.5% | Step 3.7 Flash leads |
| Gert LabsSource | 39.95% | 51.57% | Step 3.7 Flash leads |
| GDPval-AASource | 33.3% | 25.9% | GLM-4.7 leads |
| GDPval-AASource | 1165 | 1017 | GLM-4.7 leads |
| DeepSearchQASource | — | 92.8% | Not comparable |
| ToolathlonSource | — | 49.5% | Not comparable |
| Claw-EvalSource | — | 67.1% | Not comparable |
| HLE w/ toolsSource | — | 47.2% | Not comparable |
| APEX-Agents-AASource | — | 14.8% | Not comparable |
CodingGLM-4.7 wins9 benchmarks
| Benchmark | GLM-4.7 | Step 3.7 Flash | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 73.8% | — | Not comparable |
| LiveCodeBenchSource | 84.9% | — | Not comparable |
| SWE-RebenchSource | 58.7% | — | Not comparable |
| AA Coding IndexSource | 45.3% | 39.6% | GLM-4.7 leads |
| Terminal-Bench HardSource | 31.8% | 35.6% | Step 3.7 Flash leads |
| AA-SciCodeSource | 45.1% | 40.0% | GLM-4.7 leads |
| AA LiveCodeBenchSource | 89.4% | — | Not comparable |
| SWE-bench ProSource | — | 56.3% | Not comparable |
| Terminal-Bench 2.0Source | — | 59.5% | Not comparable |
Reasoning2 benchmarks
Knowledge9 benchmarks
| Benchmark | GLM-4.7 | Step 3.7 Flash | Result |
|---|---|---|---|
| GPQASource | 85.7% | — | Not comparable |
| MMLU-ProSource | 84.3% | — | Not comparable |
| HLESource | 24.8% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 33.7% | 30.3% | GLM-4.7 leads |
| AA-GPQA DiamondSource | 85.9% | 80.9% | GLM-4.7 leads |
| AA-HLESource | 25.1% | 19.9% | GLM-4.7 leads |
| AA-Omniscience IndexSource | -34.6% | -37.5% | GLM-4.7 leads |
| AA-Omniscience AccuracySource | 29.3% | 25.4% | GLM-4.7 leads |
| AA-Omniscience Hallucination RateSource | 90.3% | 84.4% | Step 3.7 Flash leads |
Math3 benchmarks
Multimodal4 benchmarks
Inst. Following1 benchmarks
| Benchmark | GLM-4.7 | Step 3.7 Flash | Result |
|---|---|---|---|
| AA-IFBenchSource | 67.9% | 67.3% | GLM-4.7 leads |
Frequently Asked Questions (3)
Which is better, GLM-4.7 or Step 3.7 Flash?
GLM-4.7 is ahead on BenchLM's provisional leaderboard, 62 to 57. The biggest single separator in this matchup is BrowseComp, where the scores are 52% and 75.8%.
Which is better for coding, GLM-4.7 or Step 3.7 Flash?
GLM-4.7 has the edge for coding in this comparison, averaging 75.4 versus 56.3. Inside this category, AA Coding Index is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, GLM-4.7 or Step 3.7 Flash?
Step 3.7 Flash has the edge for agentic tasks in this comparison, averaging 66.4 versus 45.7. Inside this category, GDPval-AA is the benchmark that creates the most daylight between them.
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