# DeepSeek-V3.1 vs Granite 3.0 2b Instruct

> DeepSeek-V3.1 is the stronger model overall, scoring 42.2 to 30.2 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v3-1-vs-granite-3-0-2b-instruct
- Last updated: 2026-10-10
- Shared benchmarks: 12

## Summary

- They share 12 benchmarks with published results for both. DeepSeek-V3.1 scores higher in 8 categories and Granite 3.0 2b Instruct in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where DeepSeek-V3.1 leads 60.5 to 29.8.

## Snapshot

| | DeepSeek-V3.1 | Granite 3.0 2b Instruct |
|---|---|---|
| Provider | DeepSeek | IBM |
| Noometry Index | 42.2 | 30.2 |
| Rank | 106 | 284 |
| Context | 164K | — |
| Input $/M | $0.25 | — |
| Output $/M | $0.95 | — |
| Weights | Open | Open |

## Coding

- DeepSeek-V3.1: 39.8 (#140)
- Granite 3.0 2b Instruct: 27.8 (#311)

| Benchmark | DeepSeek-V3.1 | Granite 3.0 2b Instruct |
|---|---|---|
| LMArena Coding | 1417 | 1090 |
| WeirdML | 38.4% | — |
| BigCodeBench Instruct | — | 20.5% |

## Reasoning

- DeepSeek-V3.1: 27.3 (#109)
- Granite 3.0 2b Instruct: 19.6 (#234)

| Benchmark | DeepSeek-V3.1 | Granite 3.0 2b Instruct |
|---|---|---|
| LMArena Hard Prompts | 1417 | 1073 |
| SimpleBench | 40% | — |
| Kagi LLM Benchmark | 53.2% | — |
| DTBench | 82.7% | — |
| LMCA | 24.3% | — |
| Epoch Capabilities Index | 139.92 | — |
| ForecastBench | 58 | — |

## Math

- DeepSeek-V3.1: 36.1 (#125)
- Granite 3.0 2b Instruct: 29.7 (#215)

| Benchmark | DeepSeek-V3.1 | Granite 3.0 2b Instruct |
|---|---|---|
| LMArena Math | 1420 | 1117 |

## Knowledge

- DeepSeek-V3.1: 43.0 (#86)
- Granite 3.0 2b Instruct: 28.4 (#238)

| Benchmark | DeepSeek-V3.1 | Granite 3.0 2b Instruct |
|---|---|---|
| LMArena Expert | 1403 | 1064 |
| Vectara Hallucination Rate | 5.5% | — |

## Multilingual

- DeepSeek-V3.1: 51.8 (#100)
- Granite 3.0 2b Instruct: 27.1 (#273)

| Benchmark | DeepSeek-V3.1 | Granite 3.0 2b Instruct |
|---|---|---|
| LMArena Non-English | 1400 | 1033 |
| LMArena Chinese | 1470 | 1070 |
| LMArena Russian | 1405 | 1045 |
| LMArena French | 1447 | — |
| LMArena German | 1412 | — |
| LMArena Japanese | 1374 | — |
| LMArena Korean | 1337 | — |
| LMArena Spanish | 1429 | — |

## Instruction Following

- DeepSeek-V3.1: 74.1 (#105)
- Granite 3.0 2b Instruct: 54.2 (#279)

| Benchmark | DeepSeek-V3.1 | Granite 3.0 2b Instruct |
|---|---|---|
| LMArena Instruction Following | 1400 | 1056 |

## Long Context

- DeepSeek-V3.1: 36.3 (#227)
- Granite 3.0 2b Instruct: 32.5 (#263)

| Benchmark | DeepSeek-V3.1 | Granite 3.0 2b Instruct |
|---|---|---|
| LMArena Longer Query | 1422 | 1071 |
| Fiction.LiveBench | 52.8% | — |

## Writing & Preference

- DeepSeek-V3.1: 60.5 (#93)
- Granite 3.0 2b Instruct: 29.8 (#287)

| Benchmark | DeepSeek-V3.1 | Granite 3.0 2b Instruct |
|---|---|---|
| LMArena Text | 1420 | 1080 |
| LMArena Creative Writing | 1401 | 1046 |
| LMArena Multi-Turn | 1408 | 1053 |
| EQ-Bench Creative Writing | 1436 | — |

## FAQ

### Is DeepSeek-V3.1 better than Granite 3.0 2b Instruct?

DeepSeek-V3.1 is the stronger model overall, scoring 42.2 to 30.2 on the Noometry Index.

### Is DeepSeek-V3.1 or Granite 3.0 2b Instruct better for coding?

DeepSeek-V3.1 scores higher on coding benchmarks: 39.8 versus 27.8 in the Noometry coding category.

### How many benchmarks do DeepSeek-V3.1 and Granite 3.0 2b Instruct share?

12 benchmarks have published results for both models. DeepSeek-V3.1 has 27 scored results on Noometry and Granite 3.0 2b Instruct has 13.