# Claude Haiku 4.5 vs Nvidia Llama 3.3 Nemotron Super 49b v1.5

> Claude Haiku 4.5 and Nvidia Llama 3.3 Nemotron Super 49b v1.5 score almost the same on the Noometry Index (39.5 vs 40.3), so choose on price, context window or the category you care about most.

- Canonical page: https://noometry.com/compare/claude-haiku-4-5-vs-nvidia-llama-3-3-nemotron-super-49b-v1-5
- Last updated: 2026-10-10
- Shared benchmarks: 12

## Summary

- They share 12 benchmarks with published results for both. Claude Haiku 4.5 scores higher in 7 categories and Nvidia Llama 3.3 Nemotron Super 49b v1.5 in 1 category; 7 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Nvidia Llama 3.3 Nemotron Super 49b v1.5 leads 26.8 to 15.1.
- Nvidia Llama 3.3 Nemotron Super 49b v1.5 is cheaper at $0.40 / $0.40 per million input/output tokens, against $1 / $5 for Claude Haiku 4.5.
- Claude Haiku 4.5 accepts more context: 200K tokens versus 131K.
- Nvidia Llama 3.3 Nemotron Super 49b v1.5 has downloadable open weights; the other is API-only.

## Snapshot

| | Claude Haiku 4.5 | Nvidia Llama 3.3 Nemotron Super 49b v1.5 |
|---|---|---|
| Provider | Anthropic | NVIDIA |
| Noometry Index | 39.5 | 40.3 |
| Rank | 165 | 151 |
| Context | 200K | 131K |
| Input $/M | $1 | $0.40 |
| Output $/M | $5 | $0.40 |
| Weights | Proprietary | Open |

## Coding

- Claude Haiku 4.5: 44.0 (#78)
- Nvidia Llama 3.3 Nemotron Super 49b v1.5: 39.8 (#154)

| Benchmark | Claude Haiku 4.5 | Nvidia Llama 3.3 Nemotron Super 49b v1.5 |
|---|---|---|
| LMArena Coding | 1453 | 1355 |
| SWE-bench Verified (bash only) | 66.6% | — |
| LMArena WebDev | 1330 | — |
| SWE-bench Multilingual | 64.7% | — |
| SciCode | 43.3% | — |
| WeirdML | 45.4% | — |
| ALE-Bench | 653.48 | — |

## Agentic & Tool Use

- Claude Haiku 4.5: 33.6 (#52)
- Nvidia Llama 3.3 Nemotron Super 49b v1.5: —

| Benchmark | Claude Haiku 4.5 | Nvidia Llama 3.3 Nemotron Super 49b v1.5 |
|---|---|---|
| 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

- Claude Haiku 4.5: 15.1 (#320)
- Nvidia Llama 3.3 Nemotron Super 49b v1.5: 26.8 (#128)

| Benchmark | Claude Haiku 4.5 | Nvidia Llama 3.3 Nemotron Super 49b v1.5 |
|---|---|---|
| LMArena Hard Prompts | 1420 | 1336 |
| 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: 44.9 (#78)
- Nvidia Llama 3.3 Nemotron Super 49b v1.5: 38.2 (#141)

| Benchmark | Claude Haiku 4.5 | Nvidia Llama 3.3 Nemotron Super 49b v1.5 |
|---|---|---|
| LMArena Math | 1396 | 1392 |
| 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

- Claude Haiku 4.5: 37.7 (#153)
- Nvidia Llama 3.3 Nemotron Super 49b v1.5: 36.7 (#165)

| Benchmark | Claude Haiku 4.5 | Nvidia Llama 3.3 Nemotron Super 49b v1.5 |
|---|---|---|
| LMArena Expert | 1442 | 1330 |
| GPQA Diamond | 71.2% | — |
| SimpleQA Verified | 13.2% | — |
| MMLU-Pro | 77.7% | — |
| Vectara Hallucination Rate | 9.8% | — |
| GPQA (HELM) | 60.5% | — |

## Multimodal

- Claude Haiku 4.5: 26.8 (#118)
- Nvidia Llama 3.3 Nemotron Super 49b v1.5: —

| Benchmark | Claude Haiku 4.5 | Nvidia Llama 3.3 Nemotron Super 49b v1.5 |
|---|---|---|
| Blueprint-Bench 2 | 0% | — |
| LMArena Document | 1420 | — |

## Multilingual

- Claude Haiku 4.5: 49.9 (#129)
- Nvidia Llama 3.3 Nemotron Super 49b v1.5: 45.5 (#168)

| Benchmark | Claude Haiku 4.5 | Nvidia Llama 3.3 Nemotron Super 49b v1.5 |
|---|---|---|
| LMArena Non-English | 1377 | 1316 |
| LMArena Japanese | 1339 | 1300 |
| LMArena Russian | 1381 | 1332 |
| LMArena Chinese | 1417 | — |
| LMArena French | 1408 | — |
| LMArena German | 1375 | — |
| LMArena Korean | 1347 | — |
| LMArena Spanish | 1420 | — |

## Instruction Following

- Claude Haiku 4.5: 71.4 (#149)
- Nvidia Llama 3.3 Nemotron Super 49b v1.5: 68.6 (#188)

| Benchmark | Claude Haiku 4.5 | Nvidia Llama 3.3 Nemotron Super 49b v1.5 |
|---|---|---|
| LMArena Instruction Following | 1414 | 1299 |
| IFEval | 80.1% | — |

## Long Context

- Claude Haiku 4.5: 43.6 (#92)
- Nvidia Llama 3.3 Nemotron Super 49b v1.5: 40.0 (#164)

| Benchmark | Claude Haiku 4.5 | Nvidia Llama 3.3 Nemotron Super 49b v1.5 |
|---|---|---|
| LMArena Longer Query | 1427 | 1315 |

## Writing & Preference

- Claude Haiku 4.5: 57.9 (#123)
- Nvidia Llama 3.3 Nemotron Super 49b v1.5: 53.1 (#159)

| Benchmark | Claude Haiku 4.5 | Nvidia Llama 3.3 Nemotron Super 49b v1.5 |
|---|---|---|
| LMArena Text | 1396 | 1338 |
| LMArena Creative Writing | 1372 | 1307 |
| LMArena Multi-Turn | 1409 | 1334 |
| WildBench | 83.9% | — |
| EQ-Bench 4 | 1064 | — |

## FAQ

### Is Claude Haiku 4.5 better than Nvidia Llama 3.3 Nemotron Super 49b v1.5?

Claude Haiku 4.5 and Nvidia Llama 3.3 Nemotron Super 49b v1.5 score almost the same on the Noometry Index (39.5 vs 40.3), so choose on price, context window or the category you care about most.

### Which is cheaper, Claude Haiku 4.5 or Nvidia Llama 3.3 Nemotron Super 49b v1.5?

Nvidia Llama 3.3 Nemotron Super 49b v1.5 is cheaper. It lists at $0.40 per million input tokens and $0.40 per million output tokens; Claude Haiku 4.5 lists at $1 and $5.

### Is Claude Haiku 4.5 or Nvidia Llama 3.3 Nemotron Super 49b v1.5 better for coding?

Claude Haiku 4.5 scores higher on coding benchmarks: 44.0 versus 39.8 in the Noometry coding category.

### Which has the bigger context window?

Claude Haiku 4.5 does, with 200K tokens against 131K.

### How many benchmarks do Claude Haiku 4.5 and Nvidia Llama 3.3 Nemotron Super 49b v1.5 share?

12 benchmarks have published results for both models. Claude Haiku 4.5 has 53 scored results on Noometry and Nvidia Llama 3.3 Nemotron Super 49b v1.5 has 12.