Model comparison
Nvidia Llama 3.3 Nemotron Super 49b v1.5 vs Qwen3.5 122B-A10B
Qwen3.5 122B-A10B is the stronger model overall, scoring 42.1 to 40.3 on the Noometry Index. Nvidia Llama 3.3 Nemotron Super 49b v1.5 costs 2.8× less per token, which makes it the better buy when Qwen3.5 122B-A10B's lead doesn't matter for your workload.
Last verified . 12 shared benchmarks.
NVIDIA
Alibaba (Qwen)Summary
- They share 12 benchmarks with published results for both. Nvidia Llama 3.3 Nemotron Super 49b v1.5 scores higher in 1 category and Qwen3.5 122B-A10B in 7 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Qwen3.5 122B-A10B leads 60.0 to 53.1.
- Nvidia Llama 3.3 Nemotron Super 49b v1.5 is cheaper at $0.40 / $0.40 per million input/output tokens, against $0.40 / $3.20 for Qwen3.5 122B-A10B.
- Qwen3.5 122B-A10B accepts more context: 262K tokens versus 131K.
Side by side
| Nvidia Llama 3.3 Nemotron Super 49b v1.5 | Qwen3.5 122B-A10B | |
|---|---|---|
| Provider | NVIDIA | Alibaba (Qwen) |
| Noometry Index | 40.3 | 42.1 |
| Released | 2025-07-25 | 2026-02-23 |
| Weights | Open | Open |
| Context window | 131K | 262K |
| Max output | 131K | 66K |
| Input $ / M tokens | $0.40 | $0.40 |
| Output $ / M tokens | $0.40 | $3.20 |
| Results tracked | 12 | 27 |
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Category by category
Coding Too close to call
Nvidia Llama 3.3 Nemotron Super 49b v1.5: 39.8 (#154), Qwen3.5 122B-A10B: 39.1 (#162)
| Benchmark | Nvidia Llama 3.3 Nemotron Super 49b v1.5 | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Coding | 1355 | 1436 |
| LMArena WebDev | — | 1360 |
| SciCode | — | 35.6% |
Reasoning Too close to call
Nvidia Llama 3.3 Nemotron Super 49b v1.5: 26.8 (#128), Qwen3.5 122B-A10B: 27.2 (#123)
| Benchmark | Nvidia Llama 3.3 Nemotron Super 49b v1.5 | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Hard Prompts | 1336 | 1421 |
| NYT Connections (extended) | — | 51.7% |
| CritPt | — | 0.9% |
| Thematic Generalization | — | 51.2% |
| Mystery Game Puzzles | — | 17% |
| DTBench | — | 84.3% |
| LMCA | — | 32.2% |
Math Too close to call
Nvidia Llama 3.3 Nemotron Super 49b v1.5: 38.2 (#141), Qwen3.5 122B-A10B: 39.1 (#112)
| Benchmark | Nvidia Llama 3.3 Nemotron Super 49b v1.5 | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Math | 1392 | 1432 |
Knowledge Qwen3.5 122B-A10B leads
Nvidia Llama 3.3 Nemotron Super 49b v1.5: 36.7 (#165), Qwen3.5 122B-A10B: 38.8 (#142)
| Benchmark | Nvidia Llama 3.3 Nemotron Super 49b v1.5 | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Expert | 1330 | 1432 |
| Vectara Hallucination Rate | — | 11.2% |
Multimodal Not comparable
Nvidia Llama 3.3 Nemotron Super 49b v1.5: —, Qwen3.5 122B-A10B: 39.6 (#57)
| Benchmark | Nvidia Llama 3.3 Nemotron Super 49b v1.5 | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Vision | — | 1245 |
Multilingual Qwen3.5 122B-A10B leads
Nvidia Llama 3.3 Nemotron Super 49b v1.5: 45.5 (#168), Qwen3.5 122B-A10B: 51.6 (#107)
| Benchmark | Nvidia Llama 3.3 Nemotron Super 49b v1.5 | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Non-English | 1316 | 1400 |
| LMArena Japanese | 1300 | 1367 |
| LMArena Russian | 1332 | 1400 |
| LMArena Chinese | — | 1462 |
| LMArena French | — | 1442 |
| LMArena German | — | 1426 |
| LMArena Korean | — | 1352 |
| LMArena Spanish | — | 1424 |
Instruction Following Qwen3.5 122B-A10B leads
Nvidia Llama 3.3 Nemotron Super 49b v1.5: 68.6 (#188), Qwen3.5 122B-A10B: 73.8 (#115)
| Benchmark | Nvidia Llama 3.3 Nemotron Super 49b v1.5 | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Instruction Following | 1299 | 1399 |
Long Context Qwen3.5 122B-A10B leads
Nvidia Llama 3.3 Nemotron Super 49b v1.5: 40.0 (#164), Qwen3.5 122B-A10B: 43.0 (#109)
| Benchmark | Nvidia Llama 3.3 Nemotron Super 49b v1.5 | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Longer Query | 1315 | 1410 |
Writing & Preference Qwen3.5 122B-A10B leads
Nvidia Llama 3.3 Nemotron Super 49b v1.5: 53.1 (#159), Qwen3.5 122B-A10B: 60.0 (#105)
| Benchmark | Nvidia Llama 3.3 Nemotron Super 49b v1.5 | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Text | 1338 | 1417 |
| LMArena Creative Writing | 1307 | 1368 |
| LMArena Multi-Turn | 1334 | 1416 |
Frequently asked questions
Is Nvidia Llama 3.3 Nemotron Super 49b v1.5 better than Qwen3.5 122B-A10B?
Qwen3.5 122B-A10B is the stronger model overall, scoring 42.1 to 40.3 on the Noometry Index. Nvidia Llama 3.3 Nemotron Super 49b v1.5 costs 2.8× less per token, which makes it the better buy when Qwen3.5 122B-A10B's lead doesn't matter for your workload.
Which is cheaper, Nvidia Llama 3.3 Nemotron Super 49b v1.5 or Qwen3.5 122B-A10B?
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; Qwen3.5 122B-A10B lists at $0.40 and $3.20.
Is Nvidia Llama 3.3 Nemotron Super 49b v1.5 or Qwen3.5 122B-A10B better for coding?
They score almost the same on coding (39.8 vs 39.1); test both on your own repository before choosing.
Which has the bigger context window?
Qwen3.5 122B-A10B does, with 262K tokens against 131K.
How many benchmarks do Nvidia Llama 3.3 Nemotron Super 49b v1.5 and Qwen3.5 122B-A10B share?
12 benchmarks have published results for both models. Nvidia Llama 3.3 Nemotron Super 49b v1.5 has 12 scored results on Noometry and Qwen3.5 122B-A10B has 27.