# GPT-4 Turbo vs Nvidia Llama 3.3 Nemotron Super 49b v1.5

> Nvidia Llama 3.3 Nemotron Super 49b v1.5 is the stronger model overall, scoring 40.3 to 30.5 on the Noometry Index.

- Canonical page: https://noometry.com/compare/gpt-4-turbo-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. GPT-4 Turbo scores higher in 0 categories and Nvidia Llama 3.3 Nemotron Super 49b v1.5 in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Nvidia Llama 3.3 Nemotron Super 49b v1.5 leads 38.2 to 9.0.
- Nvidia Llama 3.3 Nemotron Super 49b v1.5 is cheaper at $0.40 / $0.40 per million input/output tokens, against $10 / $30 for GPT-4 Turbo.
- Nvidia Llama 3.3 Nemotron Super 49b v1.5 accepts more context: 131K tokens versus 128K.
- Nvidia Llama 3.3 Nemotron Super 49b v1.5 has downloadable open weights; the other is API-only.

## Snapshot

| | GPT-4 Turbo | Nvidia Llama 3.3 Nemotron Super 49b v1.5 |
|---|---|---|
| Provider | OpenAI | NVIDIA |
| Noometry Index | 30.5 | 40.3 |
| Rank | 292 | 151 |
| Context | 128K | 131K |
| Input $/M | $10 | $0.40 |
| Output $/M | $30 | $0.40 |
| Weights | Proprietary | Open |

## Coding

- GPT-4 Turbo: 33.8 (#249)
- Nvidia Llama 3.3 Nemotron Super 49b v1.5: 39.8 (#154)

| Benchmark | GPT-4 Turbo | Nvidia Llama 3.3 Nemotron Super 49b v1.5 |
|---|---|---|
| LMArena Coding | 1268 | 1355 |
| WeirdML | 18% | — |
| BigCodeBench Instruct | 48.2% | — |
| BigCodeBench Complete | 58.2% | — |
| HumanEval+ | 86.6% | — |
| MBPP+ | 73.3% | — |

## Agentic & Tool Use

- GPT-4 Turbo: —
- Nvidia Llama 3.3 Nemotron Super 49b v1.5: —

| Benchmark | GPT-4 Turbo | Nvidia Llama 3.3 Nemotron Super 49b v1.5 |
|---|---|---|
| METR Time Horizons | 36.7% | — |

## Reasoning

- GPT-4 Turbo: 15.3 (#317)
- Nvidia Llama 3.3 Nemotron Super 49b v1.5: 26.8 (#128)

| Benchmark | GPT-4 Turbo | Nvidia Llama 3.3 Nemotron Super 49b v1.5 |
|---|---|---|
| LMArena Hard Prompts | 1251 | 1336 |
| SimpleBench | 25.1% | — |
| Chess Puzzles | 6% | — |
| DTBench | 61.6% | — |
| LMCA | 9.8% | — |
| Epoch Capabilities Index | 127.25 | — |
| ForecastBench | 59.4 | — |

## Math

- GPT-4 Turbo: 9.0 (#322)
- Nvidia Llama 3.3 Nemotron Super 49b v1.5: 38.2 (#141)

| Benchmark | GPT-4 Turbo | Nvidia Llama 3.3 Nemotron Super 49b v1.5 |
|---|---|---|
| LMArena Math | 1272 | 1392 |
| FrontierMath (Tiers 1-3) | 0.7% | — |
| OTIS Mock AIME 2024-2025 | 6.7% | — |
| MATH Level 5 | 46.7% | — |

## Knowledge

- GPT-4 Turbo: 24.3 (#268)
- Nvidia Llama 3.3 Nemotron Super 49b v1.5: 36.7 (#165)

| Benchmark | GPT-4 Turbo | Nvidia Llama 3.3 Nemotron Super 49b v1.5 |
|---|---|---|
| LMArena Expert | 1223 | 1330 |
| GPQA Diamond | 46.6% | — |
| Confabulations | 28.4% | — |
| MMLU | 81.3% | — |

## Multimodal

- GPT-4 Turbo: 30.6 (#110)
- Nvidia Llama 3.3 Nemotron Super 49b v1.5: —

| Benchmark | GPT-4 Turbo | Nvidia Llama 3.3 Nemotron Super 49b v1.5 |
|---|---|---|
| LMArena Vision | 1090 | — |

## Multilingual

- GPT-4 Turbo: 40.5 (#216)
- Nvidia Llama 3.3 Nemotron Super 49b v1.5: 45.5 (#168)

| Benchmark | GPT-4 Turbo | Nvidia Llama 3.3 Nemotron Super 49b v1.5 |
|---|---|---|
| LMArena Non-English | 1245 | 1316 |
| LMArena Japanese | 1194 | 1300 |
| LMArena Russian | 1259 | 1332 |
| LMArena Chinese | 1242 | — |
| LMArena French | 1276 | — |
| LMArena German | 1259 | — |
| LMArena Korean | 1187 | — |
| LMArena Spanish | 1260 | — |

## Instruction Following

- GPT-4 Turbo: 65.8 (#216)
- Nvidia Llama 3.3 Nemotron Super 49b v1.5: 68.6 (#188)

| Benchmark | GPT-4 Turbo | Nvidia Llama 3.3 Nemotron Super 49b v1.5 |
|---|---|---|
| LMArena Instruction Following | 1249 | 1299 |

## Long Context

- GPT-4 Turbo: 38.0 (#206)
- Nvidia Llama 3.3 Nemotron Super 49b v1.5: 40.0 (#164)

| Benchmark | GPT-4 Turbo | Nvidia Llama 3.3 Nemotron Super 49b v1.5 |
|---|---|---|
| LMArena Longer Query | 1254 | 1315 |

## Writing & Preference

- GPT-4 Turbo: 47.7 (#206)
- Nvidia Llama 3.3 Nemotron Super 49b v1.5: 53.1 (#159)

| Benchmark | GPT-4 Turbo | Nvidia Llama 3.3 Nemotron Super 49b v1.5 |
|---|---|---|
| LMArena Text | 1272 | 1338 |
| LMArena Creative Writing | 1269 | 1307 |
| LMArena Multi-Turn | 1267 | 1334 |

## FAQ

### Is GPT-4 Turbo better than Nvidia Llama 3.3 Nemotron Super 49b v1.5?

Nvidia Llama 3.3 Nemotron Super 49b v1.5 is the stronger model overall, scoring 40.3 to 30.5 on the Noometry Index.

### Which is cheaper, GPT-4 Turbo 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; GPT-4 Turbo lists at $10 and $30.

### Is GPT-4 Turbo or Nvidia Llama 3.3 Nemotron Super 49b v1.5 better for coding?

Nvidia Llama 3.3 Nemotron Super 49b v1.5 scores higher on coding benchmarks: 39.8 versus 33.8 in the Noometry coding category.

### Which has the bigger context window?

Nvidia Llama 3.3 Nemotron Super 49b v1.5 does, with 131K tokens against 128K.

### How many benchmarks do GPT-4 Turbo and Nvidia Llama 3.3 Nemotron Super 49b v1.5 share?

12 benchmarks have published results for both models. GPT-4 Turbo has 36 scored results on Noometry and Nvidia Llama 3.3 Nemotron Super 49b v1.5 has 12.