# Codellama 34b Instruct vs DeepSeek-V3.2-Exp

> DeepSeek-V3.2-Exp is the stronger model overall, scoring 44.3 to 30.8 on the Noometry Index.

- Canonical page: https://noometry.com/compare/codellama-34b-instruct-vs-deepseek-v3-2-exp
- Last updated: 2026-10-11
- Shared benchmarks: 10

## Summary

- They share 10 benchmarks with published results for both. Codellama 34b Instruct scores higher in 0 categories and DeepSeek-V3.2-Exp in 7 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where DeepSeek-V3.2-Exp leads 62.4 to 28.2.

## Snapshot

| | Codellama 34b Instruct | DeepSeek-V3.2-Exp |
|---|---|---|
| Provider | Meta | DeepSeek |
| Noometry Index | 30.8 | 44.3 |
| Rank | 287 | 78 |
| Context | — | 164K |
| Input $/M | — | $0.26 |
| Output $/M | — | $0.38 |
| Weights | Open | Open |

## Coding

- Codellama 34b Instruct: 28.5 (#314)
- DeepSeek-V3.2-Exp: 46.5 (#65)

| Benchmark | Codellama 34b Instruct | DeepSeek-V3.2-Exp |
|---|---|---|
| LMArena Coding | 1046 | 1454 |
| SWE-bench Verified (bash only) | — | 70% |
| Aider Polyglot | — | 74.2% |
| LMArena WebDev | — | 1362 |
| SWE-bench Multilingual | — | 59% |
| SciCode | — | 38.9% |
| WeirdML | — | 39.5% |
| BigCodeBench Instruct | 29% | — |
| BigCodeBench Complete | 37.1% | — |
| HumanEval+ | 43.9% | — |
| MBPP+ | 56.3% | — |

## Agentic & Tool Use

- Codellama 34b Instruct: —
- DeepSeek-V3.2-Exp: 32.7 (#59)

| Benchmark | Codellama 34b Instruct | DeepSeek-V3.2-Exp |
|---|---|---|
| Terminal-Bench | — | 39.6% |
| APEX-Agents | — | 21.3% |
| Berkeley Function Calling Leaderboard | — | 56.7% |
| TheAgentCompany | — | 42.9% |
| Vending-Bench 2 | — | 1,034 |

## Reasoning

- Codellama 34b Instruct: 19.6 (#255)
- DeepSeek-V3.2-Exp: 22.1 (#208)

| Benchmark | Codellama 34b Instruct | DeepSeek-V3.2-Exp |
|---|---|---|
| LMArena Hard Prompts | 1032 | 1434 |
| ARC-AGI-2 | — | 4% |
| Kagi LLM Benchmark | — | 52.2% |
| NYT Connections (extended) | — | 36.7% |
| ARC-AGI-1 | — | 57% |
| CritPt | — | 2.9% |
| Chess Puzzles | — | 14% |
| Thematic Generalization | — | 65% |
| DTBench | — | 87.7% |
| LMCA | — | 29.1% |
| Epoch Capabilities Index | — | 146.27 |

## Math

- Codellama 34b Instruct: 31.0 (#230)
- DeepSeek-V3.2-Exp: 41.7 (#87)

| Benchmark | Codellama 34b Instruct | DeepSeek-V3.2-Exp |
|---|---|---|
| LMArena Math | 1056 | 1435 |
| MathArena Final-Answer Competitions | — | 57.7% |
| OTIS Mock AIME 2024-2025 | — | 87.8% |
| ProofBench | — | 8% |
| FrontierMath (Feb 2025 set) | — | 22.1% |
| FrontierMath Tier 4 (v1) | — | 2.1% |

## Knowledge

- Codellama 34b Instruct: —
- DeepSeek-V3.2-Exp: 51.7 (#66)

| Benchmark | Codellama 34b Instruct | DeepSeek-V3.2-Exp |
|---|---|---|
| GPQA Diamond | — | 83.4% |
| Vectara Hallucination Rate | — | 5.3% |
| LMArena Expert | — | 1436 |

## Multilingual

- Codellama 34b Instruct: 25.8 (#284)
- DeepSeek-V3.2-Exp: 52.2 (#90)

| Benchmark | Codellama 34b Instruct | DeepSeek-V3.2-Exp |
|---|---|---|
| LMArena Non-English | 1011 | 1409 |
| LMArena Chinese | 976 | 1461 |
| LMArena French | — | 1433 |
| LMArena German | — | 1440 |
| LMArena Japanese | — | 1374 |
| LMArena Korean | — | 1371 |
| LMArena Russian | — | 1424 |
| LMArena Spanish | — | 1440 |

## Instruction Following

- Codellama 34b Instruct: 52.2 (#291)
- DeepSeek-V3.2-Exp: 74.5 (#93)

| Benchmark | Codellama 34b Instruct | DeepSeek-V3.2-Exp |
|---|---|---|
| LMArena Instruction Following | 1028 | 1413 |

## Long Context

- Codellama 34b Instruct: 30.9 (#284)
- DeepSeek-V3.2-Exp: 47.6 (#16)

| Benchmark | Codellama 34b Instruct | DeepSeek-V3.2-Exp |
|---|---|---|
| LMArena Longer Query | 1013 | 1428 |
| Fiction.LiveBench | — | 83.3% |
| CL-bench | — | 13.2% |
| CL-bench Life | — | 9.5% |

## Writing & Preference

- Codellama 34b Instruct: 28.2 (#297)
- DeepSeek-V3.2-Exp: 62.4 (#77)

| Benchmark | Codellama 34b Instruct | DeepSeek-V3.2-Exp |
|---|---|---|
| LMArena Text | 1066 | 1425 |
| LMArena Creative Writing | 1032 | 1403 |
| LMArena Multi-Turn | 1015 | 1427 |
| EQ-Bench Creative Writing | — | 1515 |

## FAQ

### Is Codellama 34b Instruct better than DeepSeek-V3.2-Exp?

DeepSeek-V3.2-Exp is the stronger model overall, scoring 44.3 to 30.8 on the Noometry Index.

### Is Codellama 34b Instruct or DeepSeek-V3.2-Exp better for coding?

DeepSeek-V3.2-Exp scores higher on coding benchmarks: 46.5 versus 28.5 in the Noometry coding category.

### How many benchmarks do Codellama 34b Instruct and DeepSeek-V3.2-Exp share?

10 benchmarks have published results for both models. Codellama 34b Instruct has 14 scored results on Noometry and DeepSeek-V3.2-Exp has 49.