# GLM-4.7-Flash vs GPT-5.1

> GPT-5.1 is the stronger model overall, scoring 49.0 to 38.8 on the Noometry Index. GLM-4.7-Flash costs 24× less per token, which makes it the better buy when GPT-5.1's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/glm-4-7-flash-vs-gpt-5-1
- Last updated: 2026-10-12
- Shared benchmarks: 20

## Summary

- They share 20 benchmarks with published results for both. GLM-4.7-Flash scores higher in 0 categories and GPT-5.1 in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-5.1 leads 39.8 to 20.9.
- The biggest single-benchmark swing is Chess Puzzles: 0% for GLM-4.7-Flash and 32% for GPT-5.1.
- GLM-4.7-Flash is cheaper at $0.06 / $0.40 per million input/output tokens, against $1.25 / $10 for GPT-5.1.
- GPT-5.1 accepts more context: 400K tokens versus 200K.
- GLM-4.7-Flash has downloadable open weights; the other is API-only.

## Snapshot

| | GLM-4.7-Flash | GPT-5.1 |
|---|---|---|
| Provider | Z.ai (Zhipu) | OpenAI |
| Noometry Index | 38.8 | 49.0 |
| Rank | 180 | 53 |
| Context | 200K | 400K |
| Input $/M | $0.06 | $1.25 |
| Output $/M | $0.40 | $10 |
| Weights | Open | Proprietary |

## Coding

- GLM-4.7-Flash: 40.6 (#135)
- GPT-5.1: 46.4 (#66)

| Benchmark | GLM-4.7-Flash | GPT-5.1 |
|---|---|---|
| LMArena Coding | 1383 | 1454 |
| SWE-bench Verified | — | 68% |
| SWE-bench Verified (bash only) | — | 66% |
| LMArena WebDev | — | 1395 |
| SciCode | — | 43.3% |
| GSO | — | 13.7% |
| WeirdML | — | 60.8% |
| LiveBench Coding | — | 72.5% |
| ALE-Bench | — | 1,192 |

## Agentic & Tool Use

- GLM-4.7-Flash: —
- GPT-5.1: 32.7 (#60)

| Benchmark | GLM-4.7-Flash | GPT-5.1 |
|---|---|---|
| Terminal-Bench | — | 47.6% |
| DeepResearch Bench | — | 42.8% |
| LMArena Search | — | 1199 |
| Vending-Bench 2 | — | 1,473 |

## Reasoning

- GLM-4.7-Flash: 20.9 (#229)
- GPT-5.1: 39.8 (#58)

| Benchmark | GLM-4.7-Flash | GPT-5.1 |
|---|---|---|
| Chess Puzzles | 0% | 32% |
| LMArena Hard Prompts | 1356 | 1457 |
| ARC-AGI-2 | — | 17.6% |
| SimpleBench | — | 53.2% |
| ARC-AGI-1 | — | 72.8% |
| CritPt | — | 4.9% |
| EnigmaEval | — | 11.2% |
| LiveBench Reasoning | — | 95.8% |
| Mystery Game Puzzles | — | 19% |
| DTBench | — | 90.1% |
| LiveBench Data Analysis | — | 72.1% |
| LMCA | — | 43.9% |
| Epoch Capabilities Index | — | 149.64 |
| ForecastBench | — | 58.1 |
| LiveBench | — | 78.8% |

## Math

- GLM-4.7-Flash: 36.1 (#173)
- GPT-5.1: 52.2 (#51)

| Benchmark | GLM-4.7-Flash | GPT-5.1 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 58.3% | 88.6% |
| LMArena Math | 1355 | 1447 |
| Omni-MATH | — | 46.4% |
| LiveBench Math | — | 94.5% |
| FrontierMath (Feb 2025 set) | — | 31% |
| FrontierMath Tier 4 (v1) | — | 12.5% |

## Knowledge

- GLM-4.7-Flash: 35.5 (#184)
- GPT-5.1: 50.6 (#71)

| Benchmark | GLM-4.7-Flash | GPT-5.1 |
|---|---|---|
| GPQA Diamond | 60.5% | 87.6% |
| Vectara Hallucination Rate | 9.3% | 10.9% |
| LMArena Expert | 1357 | 1470 |
| Humanity's Last Exam | — | 23.7% |
| SimpleQA Verified | — | 48% |
| MMLU-Pro | — | 57.9% |
| GPQA (HELM) | — | 44.2% |

## Multimodal

- GLM-4.7-Flash: —
- GPT-5.1: 44.8 (#19)

| Benchmark | GLM-4.7-Flash | GPT-5.1 |
|---|---|---|
| LMArena Vision | — | 1250 |
| VPCT | — | 58.7% |
| LMArena Document | — | 1403 |

## Multilingual

- GLM-4.7-Flash: 46.5 (#158)
- GPT-5.1: 53.8 (#56)

| Benchmark | GLM-4.7-Flash | GPT-5.1 |
|---|---|---|
| LMArena Non-English | 1330 | 1431 |
| LMArena Chinese | 1403 | 1495 |
| LMArena French | 1332 | 1450 |
| LMArena German | 1337 | 1438 |
| LMArena Korean | 1283 | 1401 |
| LMArena Russian | 1332 | 1435 |
| LMArena Spanish | 1350 | 1433 |
| LMArena Japanese | — | 1453 |

## Instruction Following

- GLM-4.7-Flash: 70.1 (#167)
- GPT-5.1: 83.9 (#1)

| Benchmark | GLM-4.7-Flash | GPT-5.1 |
|---|---|---|
| LMArena Instruction Following | 1327 | 1443 |
| LiveBench Instruction Following | — | 93.3% |
| IFEval | — | 93.5% |

## Long Context

- GLM-4.7-Flash: 40.9 (#148)
- GPT-5.1: 47.6 (#14)

| Benchmark | GLM-4.7-Flash | GPT-5.1 |
|---|---|---|
| LMArena Longer Query | 1345 | 1447 |
| CL-bench | — | 23.7% |
| CL-bench Life | — | 17.3% |

## Writing & Preference

- GLM-4.7-Flash: 47.4 (#210)
- GPT-5.1: 64.5 (#55)

| Benchmark | GLM-4.7-Flash | GPT-5.1 |
|---|---|---|
| LMArena Text | 1351 | 1443 |
| LMArena Creative Writing | 1297 | 1427 |
| LMArena Multi-Turn | 1342 | 1450 |
| EQ-Bench Creative Writing | 1125 | — |
| WildBench | — | 86.3% |
| LiveBench Language | — | 80.2% |

## FAQ

### Is GLM-4.7-Flash better than GPT-5.1?

GPT-5.1 is the stronger model overall, scoring 49.0 to 38.8 on the Noometry Index. GLM-4.7-Flash costs 24× less per token, which makes it the better buy when GPT-5.1's lead doesn't matter for your workload.

### Which is cheaper, GLM-4.7-Flash or GPT-5.1?

GLM-4.7-Flash is cheaper. It lists at $0.06 per million input tokens and $0.40 per million output tokens; GPT-5.1 lists at $1.25 and $10.

### Is GLM-4.7-Flash or GPT-5.1 better for coding?

GPT-5.1 scores higher on coding benchmarks: 46.4 versus 40.6 in the Noometry coding category.

### Which has the bigger context window?

GPT-5.1 does, with 400K tokens against 200K.

### How many benchmarks do GLM-4.7-Flash and GPT-5.1 share?

20 benchmarks have published results for both models. GLM-4.7-Flash has 21 scored results on Noometry and GPT-5.1 has 63.