Model comparison
Claude Haiku 4.5 vs Codellama 34b Instruct
Claude Haiku 4.5 is the stronger model overall, scoring 39.5 to 30.8 on the Noometry Index.
Last verified . 10 shared benchmarks.
MetaSummary
- They share 10 benchmarks with published results for both. Claude Haiku 4.5 scores higher in 6 categories and Codellama 34b Instruct in 1 category; 7 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Claude Haiku 4.5 leads 57.9 to 28.2.
- Codellama 34b Instruct has downloadable open weights; the other is API-only.
Side by side
| Claude Haiku 4.5 | Codellama 34b Instruct | |
|---|---|---|
| Provider | Anthropic | Meta |
| Noometry Index | 39.5 | 30.8 |
| Released | 2025-10-15 | — |
| Weights | Proprietary | Open |
| Context window | 200K | — |
| Max output | 64K | — |
| Input $ / M tokens | $1 | — |
| Output $ / M tokens | $5 | — |
| Results tracked | 53 | 14 |
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Category by category
Coding Claude Haiku 4.5 leads
Claude Haiku 4.5: 44.0 (#78), Codellama 34b Instruct: 28.5 (#314)
| Benchmark | Claude Haiku 4.5 | Codellama 34b Instruct |
|---|---|---|
| LMArena Coding | 1453 | 1046 |
| SWE-bench Verified (bash only) | 66.6% | — |
| LMArena WebDev | 1330 | — |
| SWE-bench Multilingual | 64.7% | — |
| SciCode | 43.3% | — |
| WeirdML | 45.4% | — |
| BigCodeBench Instruct | — | 29% |
| BigCodeBench Complete | — | 37.1% |
| ALE-Bench | 653.48 | — |
| HumanEval+ | — | 43.9% |
| MBPP+ | — | 56.3% |
Agentic & Tool Use Not comparable
Claude Haiku 4.5: 33.6 (#52), Codellama 34b Instruct: —
| Benchmark | Claude Haiku 4.5 | Codellama 34b Instruct |
|---|---|---|
| Terminal-Bench | 35.5% | — |
| Berkeley Function Calling Leaderboard | 68.7% | — |
| DeepResearch Bench | 45.5% | — |
| BALROG | 31.2% | — |
| ExploitBench | 13.7% | — |
| Vending-Bench 2 | 458.89 | — |
Reasoning Codellama 34b Instruct leads
Claude Haiku 4.5: 15.1 (#320), Codellama 34b Instruct: 19.6 (#255)
| Benchmark | Claude Haiku 4.5 | Codellama 34b Instruct |
|---|---|---|
| LMArena Hard Prompts | 1420 | 1032 |
| ARC-AGI-2 | 4% | — |
| NYT Connections (extended) | 14.3% | — |
| ARC-AGI-1 | 47.7% | — |
| CritPt | 0% | — |
| Chess Puzzles | 8% | — |
| DTBench | 73.6% | — |
| LMCA | 30.9% | — |
| Epoch Capabilities Index | 142.41 | — |
| ForecastBench | 61.4 | — |
Math Claude Haiku 4.5 leads
Claude Haiku 4.5: 44.9 (#78), Codellama 34b Instruct: 31.0 (#230)
| Benchmark | Claude Haiku 4.5 | Codellama 34b Instruct |
|---|---|---|
| LMArena Math | 1396 | 1056 |
| OTIS Mock AIME 2024-2025 | 66.7% | — |
| Omni-MATH | 56.1% | — |
| MATH Level 5 | 96.4% | — |
| FrontierMath (Feb 2025 set) | 5.9% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge Not comparable
Claude Haiku 4.5: 37.7 (#153), Codellama 34b Instruct: —
| Benchmark | Claude Haiku 4.5 | Codellama 34b Instruct |
|---|---|---|
| GPQA Diamond | 71.2% | — |
| SimpleQA Verified | 13.2% | — |
| MMLU-Pro | 77.7% | — |
| Vectara Hallucination Rate | 9.8% | — |
| GPQA (HELM) | 60.5% | — |
| LMArena Expert | 1442 | — |
Multimodal Not comparable
Claude Haiku 4.5: 26.8 (#118), Codellama 34b Instruct: —
| Benchmark | Claude Haiku 4.5 | Codellama 34b Instruct |
|---|---|---|
| Blueprint-Bench 2 | 0% | — |
| LMArena Document | 1420 | — |
Multilingual Claude Haiku 4.5 leads
Claude Haiku 4.5: 49.9 (#129), Codellama 34b Instruct: 25.8 (#284)
| Benchmark | Claude Haiku 4.5 | Codellama 34b Instruct |
|---|---|---|
| LMArena Non-English | 1377 | 1011 |
| LMArena Chinese | 1417 | 976 |
| LMArena French | 1408 | — |
| LMArena German | 1375 | — |
| LMArena Japanese | 1339 | — |
| LMArena Korean | 1347 | — |
| LMArena Russian | 1381 | — |
| LMArena Spanish | 1420 | — |
Instruction Following Claude Haiku 4.5 leads
Claude Haiku 4.5: 71.4 (#149), Codellama 34b Instruct: 52.2 (#291)
| Benchmark | Claude Haiku 4.5 | Codellama 34b Instruct |
|---|---|---|
| LMArena Instruction Following | 1414 | 1028 |
| IFEval | 80.1% | — |
Long Context Claude Haiku 4.5 leads
Claude Haiku 4.5: 43.6 (#92), Codellama 34b Instruct: 30.9 (#284)
| Benchmark | Claude Haiku 4.5 | Codellama 34b Instruct |
|---|---|---|
| LMArena Longer Query | 1427 | 1013 |
Writing & Preference Claude Haiku 4.5 leads
Claude Haiku 4.5: 57.9 (#123), Codellama 34b Instruct: 28.2 (#297)
| Benchmark | Claude Haiku 4.5 | Codellama 34b Instruct |
|---|---|---|
| LMArena Text | 1396 | 1066 |
| LMArena Creative Writing | 1372 | 1032 |
| LMArena Multi-Turn | 1409 | 1015 |
| WildBench | 83.9% | — |
| EQ-Bench 4 | 1064 | — |
Frequently asked questions
Is Claude Haiku 4.5 better than Codellama 34b Instruct?
Claude Haiku 4.5 is the stronger model overall, scoring 39.5 to 30.8 on the Noometry Index.
Is Claude Haiku 4.5 or Codellama 34b Instruct better for coding?
Claude Haiku 4.5 scores higher on coding benchmarks: 44.0 versus 28.5 in the Noometry coding category.
How many benchmarks do Claude Haiku 4.5 and Codellama 34b Instruct share?
10 benchmarks have published results for both models. Claude Haiku 4.5 has 53 scored results on Noometry and Codellama 34b Instruct has 14.