# DeepSeek-V3.1-Terminus vs GLM-5.3

> GLM-5.3 is the stronger model overall, scoring 54.6 to 42.6 on the Noometry Index. DeepSeek-V3.1-Terminus costs 4.5× less per token, which makes it the better buy when GLM-5.3's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/deepseek-v3-1-terminus-vs-glm-5-3
- Last updated: 2026-10-10
- Shared benchmarks: 15

## Summary

- They share 15 benchmarks with published results for both. DeepSeek-V3.1-Terminus scores higher in 0 categories and GLM-5.3 in 7 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in math, where GLM-5.3 leads 62.1 to 35.7.
- The biggest single-benchmark swing is LMCA: 28.6% for DeepSeek-V3.1-Terminus and 55.5% for GLM-5.3.
- DeepSeek-V3.1-Terminus is cheaper at $0.30 / $1 per million input/output tokens, against $1.40 / $4.40 for GLM-5.3.
- GLM-5.3 accepts more context: 1M tokens versus 164K.

## Snapshot

| | DeepSeek-V3.1-Terminus | GLM-5.3 |
|---|---|---|
| Provider | DeepSeek | Z.ai (Zhipu) |
| Noometry Index | 42.6 | 54.6 |
| Rank | 96 | 25 |
| Context | 164K | 1M |
| Input $/M | $0.30 | $1.40 |
| Output $/M | $1 | $4.40 |
| Weights | Open | Open |

## Coding

- DeepSeek-V3.1-Terminus: 41.5 (#114)
- GLM-5.3: 59.0 (#12)

| Benchmark | DeepSeek-V3.1-Terminus | GLM-5.3 |
|---|---|---|
| SciCode | 40.6% | 59% |
| LMArena Coding | 1426 | 1499 |
| ALE-Bench | 745.17 | 1,317 |
| DeepSWE | — | 69% |
| FrontierCode | — | 40.1% |
| LMArena WebDev | — | 1623 |
| FrontierSWE | — | 30.2% |
| WeirdML | — | 75.4% |

## Agentic & Tool Use

- DeepSeek-V3.1-Terminus: —
- GLM-5.3: 36.3 (#34)

| Benchmark | DeepSeek-V3.1-Terminus | GLM-5.3 |
|---|---|---|
| APEX-Agents | — | 56.6% |
| Vending-Bench 2 | — | 8,164 |

## Reasoning

- DeepSeek-V3.1-Terminus: 25.7 (#126)
- GLM-5.3: 45.2 (#42)

| Benchmark | DeepSeek-V3.1-Terminus | GLM-5.3 |
|---|---|---|
| CritPt | 1.7% | 19.1% |
| LMArena Hard Prompts | 1427 | 1491 |
| DTBench | 81.3% | 87.7% |
| LMCA | 28.6% | 55.5% |
| Kagi LLM Benchmark | 57.4% | — |
| NYT Connections (extended) | — | 74.2% |
| Chess Puzzles | — | 21% |
| Mystery Game Puzzles | — | 33% |
| Bench to the Future 3 | — | 0.15 |
| Epoch Capabilities Index | — | 155.56 |

## Math

- DeepSeek-V3.1-Terminus: 35.7 (#138)
- GLM-5.3: 62.1 (#27)

| Benchmark | DeepSeek-V3.1-Terminus | GLM-5.3 |
|---|---|---|
| LMArena Math | 1402 | 1493 |
| FrontierMath (Tiers 1-3) | — | 68.8% |
| FrontierMath Tier 4 | — | 29.3% |
| OTIS Mock AIME 2024-2025 | — | 91.1% |
| ProofBench | — | 49% |

## Knowledge

- DeepSeek-V3.1-Terminus: —
- GLM-5.3: 58.3 (#34)

| Benchmark | DeepSeek-V3.1-Terminus | GLM-5.3 |
|---|---|---|
| GPQA Diamond | — | 90.9% |
| SimpleQA Verified | — | 41% |
| LMArena Expert | — | 1512 |

## Multilingual

- DeepSeek-V3.1-Terminus: 52.3 (#87)
- GLM-5.3: 55.9 (#27)

| Benchmark | DeepSeek-V3.1-Terminus | GLM-5.3 |
|---|---|---|
| LMArena Non-English | 1407 | 1457 |
| LMArena Russian | 1434 | 1460 |
| LMArena Chinese | — | 1523 |
| LMArena French | — | 1499 |
| LMArena German | — | 1505 |
| LMArena Japanese | — | 1438 |
| LMArena Korean | — | 1478 |
| LMArena Spanish | — | 1444 |

## Instruction Following

- DeepSeek-V3.1-Terminus: 74.4 (#96)
- GLM-5.3: 77.8 (#15)

| Benchmark | DeepSeek-V3.1-Terminus | GLM-5.3 |
|---|---|---|
| LMArena Instruction Following | 1406 | 1481 |

## Long Context

- DeepSeek-V3.1-Terminus: 43.5 (#88)
- GLM-5.3: 45.5 (#32)

| Benchmark | DeepSeek-V3.1-Terminus | GLM-5.3 |
|---|---|---|
| LMArena Longer Query | 1426 | 1485 |

## Writing & Preference

- DeepSeek-V3.1-Terminus: 61.3 (#87)
- GLM-5.3: 75.9 (#6)

| Benchmark | DeepSeek-V3.1-Terminus | GLM-5.3 |
|---|---|---|
| LMArena Text | 1420 | 1473 |
| LMArena Creative Writing | 1404 | 1459 |
| LMArena Multi-Turn | 1411 | 1473 |
| EQ-Bench Creative Writing | — | 2075 |

## FAQ

### Is DeepSeek-V3.1-Terminus better than GLM-5.3?

GLM-5.3 is the stronger model overall, scoring 54.6 to 42.6 on the Noometry Index. DeepSeek-V3.1-Terminus costs 4.5× less per token, which makes it the better buy when GLM-5.3's lead doesn't matter for your workload.

### Which is cheaper, DeepSeek-V3.1-Terminus or GLM-5.3?

DeepSeek-V3.1-Terminus is cheaper. It lists at $0.30 per million input tokens and $1 per million output tokens; GLM-5.3 lists at $1.40 and $4.40.

### Is DeepSeek-V3.1-Terminus or GLM-5.3 better for coding?

GLM-5.3 scores higher on coding benchmarks: 59.0 versus 41.5 in the Noometry coding category.

### Which has the bigger context window?

GLM-5.3 does, with 1M tokens against 164K.

### How many benchmarks do DeepSeek-V3.1-Terminus and GLM-5.3 share?

15 benchmarks have published results for both models. DeepSeek-V3.1-Terminus has 16 scored results on Noometry and GLM-5.3 has 41.