# DeepSeek-V3.1-Terminus vs Qwen-14B

> DeepSeek-V3.1-Terminus is the stronger model overall, scoring 43.1 to 31.4 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v3-1-terminus-vs-qwen-14b
- Last updated: 2026-10-10
- Shared benchmarks: 9

## Summary

- They share 9 benchmarks with published results for both. DeepSeek-V3.1-Terminus scores higher in 7 categories and Qwen-14B in 0 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where DeepSeek-V3.1-Terminus leads 61.0 to 27.6.

## Snapshot

| | DeepSeek-V3.1-Terminus | Qwen-14B |
|---|---|---|
| Provider | DeepSeek | Alibaba (Qwen) |
| Noometry Index | 43.1 | 31.4 |
| Rank | 97 | 275 |
| Context | 164K | — |
| Input $/M | $0.27 | — |
| Output $/M | $1 | — |
| Weights | Open | Open |

## Coding

- DeepSeek-V3.1-Terminus: 42.0 (#113)
- Qwen-14B: 31.2 (#288)

| Benchmark | DeepSeek-V3.1-Terminus | Qwen-14B |
|---|---|---|
| LMArena Coding | 1426 | 1071 |
| SciCode | 40.6% | — |
| ALE-Bench | 745.17 | — |

## Reasoning

- DeepSeek-V3.1-Terminus: 26.4 (#133)
- Qwen-14B: 19.6 (#257)

| Benchmark | DeepSeek-V3.1-Terminus | Qwen-14B |
|---|---|---|
| LMArena Hard Prompts | 1426 | 1027 |
| Kagi LLM Benchmark | 57.4% | — |
| CritPt | 1.7% | — |
| DTBench | 81.3% | — |
| LMCA | 28.6% | — |
| BIG-Bench Hard | — | 55% |
| Epoch Capabilities Index | — | 113.03 |
| LAMBADA | — | 71.1% |
| PIQA | — | 79.9% |

## Math

- DeepSeek-V3.1-Terminus: 38.5 (#137)
- Qwen-14B: 31.2 (#227)

| Benchmark | DeepSeek-V3.1-Terminus | Qwen-14B |
|---|---|---|
| LMArena Math | 1402 | 1068 |
| GSM8K | — | 61.3% |

## Knowledge

- DeepSeek-V3.1-Terminus: —
- Qwen-14B: —

| Benchmark | DeepSeek-V3.1-Terminus | Qwen-14B |
|---|---|---|
| ARC (AI2) Challenge | — | 84.4% |
| BoolQ | — | 86.2% |
| MMLU | — | 66.3% |

## Multilingual

- DeepSeek-V3.1-Terminus: 52.1 (#92)
- Qwen-14B: 27.5 (#275)

| Benchmark | DeepSeek-V3.1-Terminus | Qwen-14B |
|---|---|---|
| LMArena Non-English | 1407 | 1041 |
| LMArena Chinese | — | 1077 |
| LMArena Russian | 1436 | — |

## Instruction Following

- DeepSeek-V3.1-Terminus: 74.0 (#106)
- Qwen-14B: 52.4 (#289)

| Benchmark | DeepSeek-V3.1-Terminus | Qwen-14B |
|---|---|---|
| LMArena Instruction Following | 1404 | 1031 |

## Long Context

- DeepSeek-V3.1-Terminus: 43.4 (#97)
- Qwen-14B: 31.3 (#280)

| Benchmark | DeepSeek-V3.1-Terminus | Qwen-14B |
|---|---|---|
| LMArena Longer Query | 1421 | 1028 |

## Writing & Preference

- DeepSeek-V3.1-Terminus: 61.0 (#92)
- Qwen-14B: 27.6 (#299)

| Benchmark | DeepSeek-V3.1-Terminus | Qwen-14B |
|---|---|---|
| LMArena Text | 1419 | 1051 |
| LMArena Creative Writing | 1403 | 1028 |
| LMArena Multi-Turn | 1411 | 1022 |

## FAQ

### Is DeepSeek-V3.1-Terminus better than Qwen-14B?

DeepSeek-V3.1-Terminus is the stronger model overall, scoring 43.1 to 31.4 on the Noometry Index.

### Is DeepSeek-V3.1-Terminus or Qwen-14B better for coding?

DeepSeek-V3.1-Terminus scores higher on coding benchmarks: 42.0 versus 31.2 in the Noometry coding category.

### How many benchmarks do DeepSeek-V3.1-Terminus and Qwen-14B share?

9 benchmarks have published results for both models. DeepSeek-V3.1-Terminus has 16 scored results on Noometry and Qwen-14B has 18.