# DeepSeek-V3.1 vs Yi-34B

> DeepSeek-V3.1 is the stronger model overall, scoring 42.2 to 27.4 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v3-1-vs-yi-34b
- Last updated: 2026-10-10
- Shared benchmarks: 18

## Summary

- They share 18 benchmarks with published results for both. DeepSeek-V3.1 scores higher in 8 categories and Yi-34B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where DeepSeek-V3.1 leads 43.0 to 7.5.

## Snapshot

| | DeepSeek-V3.1 | Yi-34B |
|---|---|---|
| Provider | DeepSeek | 01.AI |
| Noometry Index | 42.2 | 27.4 |
| Rank | 106 | 325 |
| Context | 164K | — |
| Input $/M | $0.25 | — |
| Output $/M | $0.95 | — |
| Weights | Open | Open |

## Coding

- DeepSeek-V3.1: 39.8 (#140)
- Yi-34B: 31.8 (#269)

| Benchmark | DeepSeek-V3.1 | Yi-34B |
|---|---|---|
| LMArena Coding | 1417 | 1112 |
| WeirdML | 38.4% | — |

## Reasoning

- DeepSeek-V3.1: 27.3 (#109)
- Yi-34B: 20.3 (#222)

| Benchmark | DeepSeek-V3.1 | Yi-34B |
|---|---|---|
| LMArena Hard Prompts | 1417 | 1104 |
| Epoch Capabilities Index | 139.92 | 117.28 |
| SimpleBench | 40% | — |
| Kagi LLM Benchmark | 53.2% | — |
| DTBench | 82.7% | — |
| LMCA | 24.3% | — |
| BIG-Bench Hard | — | 71.7% |
| ForecastBench | 58 | — |

## Math

- DeepSeek-V3.1: 36.1 (#125)
- Yi-34B: 19.8 (#277)

| Benchmark | DeepSeek-V3.1 | Yi-34B |
|---|---|---|
| LMArena Math | 1420 | 1114 |
| MATH Level 5 | — | 5.1% |
| GSM8K | — | 76% |

## Knowledge

- DeepSeek-V3.1: 43.0 (#86)
- Yi-34B: 7.5 (#304)

| Benchmark | DeepSeek-V3.1 | Yi-34B |
|---|---|---|
| LMArena Expert | 1403 | 1061 |
| GPQA Diamond | — | 14.7% |
| Vectara Hallucination Rate | 5.5% | — |
| MMLU | — | 76.3% |

## Multilingual

- DeepSeek-V3.1: 51.8 (#100)
- Yi-34B: 29.9 (#259)

| Benchmark | DeepSeek-V3.1 | Yi-34B |
|---|---|---|
| LMArena Non-English | 1400 | 1079 |
| LMArena Chinese | 1470 | 1175 |
| LMArena French | 1447 | 1080 |
| LMArena German | 1412 | 1042 |
| LMArena Japanese | 1374 | 993 |
| LMArena Korean | 1337 | 959 |
| LMArena Russian | 1405 | 1050 |
| LMArena Spanish | 1429 | 1070 |

## Instruction Following

- DeepSeek-V3.1: 74.1 (#105)
- Yi-34B: 56.4 (#269)

| Benchmark | DeepSeek-V3.1 | Yi-34B |
|---|---|---|
| LMArena Instruction Following | 1400 | 1091 |

## Long Context

- DeepSeek-V3.1: 36.3 (#227)
- Yi-34B: 33.2 (#259)

| Benchmark | DeepSeek-V3.1 | Yi-34B |
|---|---|---|
| LMArena Longer Query | 1422 | 1094 |
| Fiction.LiveBench | 52.8% | — |

## Writing & Preference

- DeepSeek-V3.1: 60.5 (#93)
- Yi-34B: 34.3 (#268)

| Benchmark | DeepSeek-V3.1 | Yi-34B |
|---|---|---|
| LMArena Text | 1420 | 1129 |
| LMArena Creative Writing | 1401 | 1108 |
| LMArena Multi-Turn | 1408 | 1113 |
| EQ-Bench Creative Writing | 1436 | — |

## FAQ

### Is DeepSeek-V3.1 better than Yi-34B?

DeepSeek-V3.1 is the stronger model overall, scoring 42.2 to 27.4 on the Noometry Index.

### Is DeepSeek-V3.1 or Yi-34B better for coding?

DeepSeek-V3.1 scores higher on coding benchmarks: 39.8 versus 31.8 in the Noometry coding category.

### How many benchmarks do DeepSeek-V3.1 and Yi-34B share?

18 benchmarks have published results for both models. DeepSeek-V3.1 has 27 scored results on Noometry and Yi-34B has 23.