Model comparison
GLM-4.7 vs Grok Code Fast 1
Head-to-head evidence from 13 shared benchmark results across 5 categories. Overall scores shown here use BenchLM's provisional ranking lane.
Verified leaderboard positions: GLM-4.7 #32; Grok Code Fast 1 unranked
Evidence parity. GLM-4.7 and Grok Code Fast 1 share 13 comparable benchmark results. 1 of 8 categories are comparable. 18 results are unique to GLM-4.7; 0 to Grok Code Fast 1.
Updated July 14, 2026- Shared results
- 13
- GLM-4.7 only
- 18
- Grok Code Fast 1 only
- 0
- Comparable categories
- 1 / 8
Pick GLM-4.7 if you want the stronger benchmark profile. Grok Code Fast 1 only becomes the better choice if you need the larger 256K context window or you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 13 shared benchmark results across 5 evidence categories; 1 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 40. 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 73.8 against 70.8. The single biggest benchmark swing on the page is SWE-bench Verified, 73.8% to 70.8%.
Grok Code Fast 1 is also the more expensive model on tokens at $0.20 input / $1.50 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. GLM-4.7 is the reasoning model in the pair, while Grok Code Fast 1 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Grok Code Fast 1 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 | Grok Code Fast 1 |
|---|---|---|---|
| Coding | GLM-4.773.8 | Margin← 3.0 | Grok Code Fast 170.8 |
| Agentic | GLM-4.745.7 | MarginNo overlap | Grok Code Fast 1Not measured |
| Knowledge | GLM-4.752.1 | MarginNo overlap | Grok Code Fast 1Not measured |
| Math | GLM-4.71.8 | MarginNo overlap | Grok Code Fast 1Not measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
SWE-bench Verified
CodingA 73.8%B 70.8%Winner: GLM-4.7Δ 3SWE-bench Verified: GLM-4.7 scored 73.8%; Grok Code Fast 1 scored 70.8%. GLM-4.7 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GLM-4.7 | Grok Code Fast 1 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GLM-4.7$0 input / $0 output | Grok Code Fast 1$0.2 input / $1.5 output | GLM-4.7 has the lower combined listed price. |
| Generation speedtokens per second | GLM-4.782 tok/s | Grok Code Fast 1172 tok/s | Grok Code Fast 1 has the higher measured throughput. |
| First-answer latencyseconds to first token | GLM-4.71.10 s | Grok Code Fast 12.81 s | GLM-4.7 reaches the first token sooner. |
| Context windowmaximum listed tokens | GLM-4.7200K | Grok Code Fast 1256K | Grok Code Fast 1 lists the larger context window. |
Benchmark Deep Dive
Agentic8 benchmarks
| Benchmark | GLM-4.7 | Grok Code Fast 1 | 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 |
| Tau2-TelecomSource | 95.9% | 75.7% | GLM-4.7 leads |
| Gert LabsSource | 39.95% | — | Not comparable |
| GDPval-AASource | 33.3% | — | Not comparable |
| GDPval-AASource | 1165 | — | Not comparable |
CodingGLM-4.7 wins7 benchmarks
| Benchmark | GLM-4.7 | Grok Code Fast 1 | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 73.8% | 70.8% | GLM-4.7 leads |
| LiveCodeBenchSource | 84.9% | — | Not comparable |
| SWE-RebenchSource | 58.7% | — | Not comparable |
| AA Coding IndexSource | 45.3% | — | Not comparable |
| Terminal-Bench HardSource | 31.8% | 17.4% | GLM-4.7 leads |
| AA-SciCodeSource | 45.1% | 36.2% | GLM-4.7 leads |
| AA LiveCodeBenchSource | 89.4% | — | Not comparable |
Reasoning2 benchmarks
Knowledge9 benchmarks
| Benchmark | GLM-4.7 | Grok Code Fast 1 | Result |
|---|---|---|---|
| GPQASource | 85.7% | — | Not comparable |
| MMLU-ProSource | 84.3% | — | Not comparable |
| HLESource | 24.8% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 33.7% | 21.6% | GLM-4.7 leads |
| AA-GPQA DiamondSource | 85.9% | 72.7% | GLM-4.7 leads |
| AA-HLESource | 25.1% | 7.5% | GLM-4.7 leads |
| AA-Omniscience IndexSource | -34.6% | -36.0% | GLM-4.7 leads |
| AA-Omniscience AccuracySource | 29.3% | 23.8% | GLM-4.7 leads |
| AA-Omniscience Hallucination RateSource | 90.3% | 78.5% | Grok Code Fast 1 leads |
Math3 benchmarks
Multimodal1 benchmarks
| Benchmark | GLM-4.7 | Grok Code Fast 1 | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1260 | — | Not comparable |
Inst. Following1 benchmarks
| Benchmark | GLM-4.7 | Grok Code Fast 1 | Result |
|---|---|---|---|
| AA-IFBenchSource | 67.9% | 41.4% | GLM-4.7 leads |
Frequently Asked Questions (2)
Which is better, GLM-4.7 or Grok Code Fast 1?
GLM-4.7 is ahead on BenchLM's provisional leaderboard, 62 to 40. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 73.8% and 70.8%.
Which is better for coding, GLM-4.7 or Grok Code Fast 1?
GLM-4.7 has the edge for coding in this comparison, averaging 73.8 versus 70.8. Inside this category, Terminal-Bench Hard is the benchmark that creates the most daylight between them.
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