# GLM-4.7-Flash vs GPT-6.1 Sol

> GPT-6.1 Sol is the stronger model overall, scoring 65.6 to 38.8 on the Noometry Index. GLM-4.7-Flash costs 28× less per token, which makes it the better buy when GPT-6.1 Sol's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/glm-4-7-flash-vs-gpt-6-1-sol
- Last updated: 2026-10-12
- Shared benchmarks: 15

## Summary

- They share 15 benchmarks with published results for both. GLM-4.7-Flash scores higher in 0 categories and GPT-6.1 Sol in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-6.1 Sol leads 81.9 to 20.9.
- The biggest single-benchmark swing is Chess Puzzles: 0% for GLM-4.7-Flash and 61% for GPT-6.1 Sol.
- GLM-4.7-Flash is cheaper at $0.06 / $0.40 per million input/output tokens, against $2 / $10 for GPT-6.1 Sol.
- GPT-6.1 Sol accepts more context: 1.05M tokens versus 200K.
- GLM-4.7-Flash has downloadable open weights; the other is API-only.

## Snapshot

| | GLM-4.7-Flash | GPT-6.1 Sol |
|---|---|---|
| Provider | Z.ai (Zhipu) | OpenAI |
| Noometry Index | 38.8 | 65.6 |
| Rank | 180 | 6 |
| Context | 200K | 1.05M |
| Input $/M | $0.06 | $2 |
| Output $/M | $0.40 | $10 |
| Weights | Open | Proprietary |

## Coding

- GLM-4.7-Flash: 40.6 (#135)
- GPT-6.1 Sol: 63.2 (#8)

| Benchmark | GLM-4.7-Flash | GPT-6.1 Sol |
|---|---|---|
| LMArena Coding | 1383 | 1487 |
| DeepSWE | — | 75.2% |
| FrontierCode | — | 50.2% |
| LMArena WebDev | — | 1755 |
| SciCode | — | 55.8% |

## Agentic & Tool Use

- GLM-4.7-Flash: —
- GPT-6.1 Sol: 39.6 (#26)

| Benchmark | GLM-4.7-Flash | GPT-6.1 Sol |
|---|---|---|
| APEX-Agents | — | 60% |
| GDP.pdf | — | 32% |

## Reasoning

- GLM-4.7-Flash: 20.9 (#229)
- GPT-6.1 Sol: 81.9 (#2)

| Benchmark | GLM-4.7-Flash | GPT-6.1 Sol |
|---|---|---|
| Chess Puzzles | 0% | 61% |
| LMArena Hard Prompts | 1356 | 1466 |
| ARC-AGI-2 | — | 94.2% |
| NYT Connections (extended) | — | 95.5% |
| ARC-AGI-1 | — | 98.5% |
| CritPt | — | 31.7% |
| EBR-Bench | — | 54.3% |
| Mystery Game Puzzles | — | 80% |
| Epoch Capabilities Index | — | 166.09 |

## Math

- GLM-4.7-Flash: 36.1 (#173)
- GPT-6.1 Sol: 93.7 (#1)

| Benchmark | GLM-4.7-Flash | GPT-6.1 Sol |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 58.3% | 100% |
| LMArena Math | 1355 | 1464 |
| FrontierMath (Tiers 1-3) | — | 93.7% |
| FrontierMath Tier 4 | — | 100% |
| ProofBench | — | 99% |

## Knowledge

- GLM-4.7-Flash: 35.5 (#184)
- GPT-6.1 Sol: 71.8 (#4)

| Benchmark | GLM-4.7-Flash | GPT-6.1 Sol |
|---|---|---|
| GPQA Diamond | 60.5% | 95.4% |
| LMArena Expert | 1357 | 1502 |
| SimpleQA Verified | — | 73.9% |
| Vectara Hallucination Rate | 9.3% | — |

## Multimodal

- GLM-4.7-Flash: —
- GPT-6.1 Sol: 52.7 (#5)

| Benchmark | GLM-4.7-Flash | GPT-6.1 Sol |
|---|---|---|
| LMArena Vision | — | 1288 |
| Furniture Assembly | — | 80% |

## Multilingual

- GLM-4.7-Flash: 46.5 (#158)
- GPT-6.1 Sol: 54.3 (#46)

| Benchmark | GLM-4.7-Flash | GPT-6.1 Sol |
|---|---|---|
| LMArena Non-English | 1330 | 1438 |
| LMArena Chinese | 1403 | 1477 |
| LMArena Russian | 1332 | 1455 |
| LMArena French | 1332 | — |
| LMArena German | 1337 | — |
| LMArena Korean | 1283 | — |
| LMArena Spanish | 1350 | — |

## Instruction Following

- GLM-4.7-Flash: 70.1 (#167)
- GPT-6.1 Sol: 77.0 (#29)

| Benchmark | GLM-4.7-Flash | GPT-6.1 Sol |
|---|---|---|
| LMArena Instruction Following | 1327 | 1468 |

## Long Context

- GLM-4.7-Flash: 40.9 (#148)
- GPT-6.1 Sol: 44.9 (#54)

| Benchmark | GLM-4.7-Flash | GPT-6.1 Sol |
|---|---|---|
| LMArena Longer Query | 1345 | 1465 |

## Writing & Preference

- GLM-4.7-Flash: 47.4 (#210)
- GPT-6.1 Sol: 63.6 (#63)

| Benchmark | GLM-4.7-Flash | GPT-6.1 Sol |
|---|---|---|
| LMArena Text | 1351 | 1447 |
| LMArena Creative Writing | 1297 | 1432 |
| LMArena Multi-Turn | 1342 | 1449 |
| EQ-Bench Creative Writing | 1125 | — |

## FAQ

### Is GLM-4.7-Flash better than GPT-6.1 Sol?

GPT-6.1 Sol is the stronger model overall, scoring 65.6 to 38.8 on the Noometry Index. GLM-4.7-Flash costs 28× less per token, which makes it the better buy when GPT-6.1 Sol's lead doesn't matter for your workload.

### Which is cheaper, GLM-4.7-Flash or GPT-6.1 Sol?

GLM-4.7-Flash is cheaper. It lists at $0.06 per million input tokens and $0.40 per million output tokens; GPT-6.1 Sol lists at $2 and $10.

### Is GLM-4.7-Flash or GPT-6.1 Sol better for coding?

GPT-6.1 Sol scores higher on coding benchmarks: 63.2 versus 40.6 in the Noometry coding category.

### Which has the bigger context window?

GPT-6.1 Sol does, with 1.05M tokens against 200K.

### How many benchmarks do GLM-4.7-Flash and GPT-6.1 Sol share?

15 benchmarks have published results for both models. GLM-4.7-Flash has 21 scored results on Noometry and GPT-6.1 Sol has 34.