# DeepSeek-V3.1-Terminus vs GLM-4.6V

> DeepSeek-V3.1-Terminus is the stronger model overall, scoring 43.1 to 41.3 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v3-1-terminus-vs-glm-4-6v
- Last updated: 2026-10-12
- Shared benchmarks: 9

## Summary

- They share 9 benchmarks with published results for both. DeepSeek-V3.1-Terminus scores higher in 5 categories and GLM-4.6V in 1 category; 6 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where DeepSeek-V3.1-Terminus leads 61.0 to 56.6.
- Both cost about the same: $0.27 input and $1 output per million tokens.
- DeepSeek-V3.1-Terminus accepts more context: 164K tokens versus 128K.

## Snapshot

| | DeepSeek-V3.1-Terminus | GLM-4.6V |
|---|---|---|
| Provider | DeepSeek | Z.ai (Zhipu) |
| Noometry Index | 43.1 | 41.3 |
| Rank | 97 | 137 |
| Context | 164K | 128K |
| Input $/M | $0.27 | $0.30 |
| Output $/M | $1 | $0.90 |
| Weights | Open | Open |

## Coding

- DeepSeek-V3.1-Terminus: 42.0 (#113)
- GLM-4.6V: 40.9 (#128)

| Benchmark | DeepSeek-V3.1-Terminus | GLM-4.6V |
|---|---|---|
| LMArena Coding | 1426 | 1390 |
| SciCode | 40.6% | — |
| ALE-Bench | 745.17 | — |

## Reasoning

- DeepSeek-V3.1-Terminus: 26.4 (#133)
- GLM-4.6V: 27.6 (#115)

| Benchmark | DeepSeek-V3.1-Terminus | GLM-4.6V |
|---|---|---|
| LMArena Hard Prompts | 1426 | 1368 |
| Kagi LLM Benchmark | 57.4% | — |
| CritPt | 1.7% | — |
| DTBench | 81.3% | — |
| LMCA | 28.6% | — |

## Math

- DeepSeek-V3.1-Terminus: 38.5 (#137)
- GLM-4.6V: —

| Benchmark | DeepSeek-V3.1-Terminus | GLM-4.6V |
|---|---|---|
| LMArena Math | 1402 | — |

## Knowledge

- DeepSeek-V3.1-Terminus: —
- GLM-4.6V: 38.0 (#149)

| Benchmark | DeepSeek-V3.1-Terminus | GLM-4.6V |
|---|---|---|
| LMArena Expert | — | 1371 |

## Multimodal

- DeepSeek-V3.1-Terminus: —
- GLM-4.6V: 34.8 (#90)

| Benchmark | DeepSeek-V3.1-Terminus | GLM-4.6V |
|---|---|---|
| LMArena Vision | — | 1164 |

## Multilingual

- DeepSeek-V3.1-Terminus: 52.1 (#92)
- GLM-4.6V: 48.6 (#141)

| Benchmark | DeepSeek-V3.1-Terminus | GLM-4.6V |
|---|---|---|
| LMArena Non-English | 1407 | 1359 |
| LMArena Russian | 1436 | 1340 |
| LMArena Chinese | — | 1425 |

## Instruction Following

- DeepSeek-V3.1-Terminus: 74.0 (#106)
- GLM-4.6V: 71.4 (#151)

| Benchmark | DeepSeek-V3.1-Terminus | GLM-4.6V |
|---|---|---|
| LMArena Instruction Following | 1404 | 1352 |

## Long Context

- DeepSeek-V3.1-Terminus: 43.4 (#97)
- GLM-4.6V: 41.3 (#143)

| Benchmark | DeepSeek-V3.1-Terminus | GLM-4.6V |
|---|---|---|
| LMArena Longer Query | 1421 | 1358 |

## Writing & Preference

- DeepSeek-V3.1-Terminus: 61.0 (#92)
- GLM-4.6V: 56.6 (#137)

| Benchmark | DeepSeek-V3.1-Terminus | GLM-4.6V |
|---|---|---|
| LMArena Text | 1419 | 1377 |
| LMArena Creative Writing | 1403 | 1347 |
| LMArena Multi-Turn | 1411 | 1360 |

## FAQ

### Is DeepSeek-V3.1-Terminus better than GLM-4.6V?

DeepSeek-V3.1-Terminus is the stronger model overall, scoring 43.1 to 41.3 on the Noometry Index.

### Which is cheaper, DeepSeek-V3.1-Terminus or GLM-4.6V?

GLM-4.6V is cheaper. It lists at $0.30 per million input tokens and $0.90 per million output tokens; DeepSeek-V3.1-Terminus lists at $0.27 and $1.

### Is DeepSeek-V3.1-Terminus or GLM-4.6V better for coding?

DeepSeek-V3.1-Terminus scores higher on coding benchmarks: 42.0 versus 40.9 in the Noometry coding category.

### Which has the bigger context window?

DeepSeek-V3.1-Terminus does, with 164K tokens against 128K.

### How many benchmarks do DeepSeek-V3.1-Terminus and GLM-4.6V share?

9 benchmarks have published results for both models. DeepSeek-V3.1-Terminus has 16 scored results on Noometry and GLM-4.6V has 12.