Seed-OSS-36B-Instruct vs Llama 3.3 Nemotron Super 49B v1.5
Seed-OSS-36B-Instruct comes out ahead, 40 to 31 on our weighted score.
- Our pick
ByteDance SeedSeed-OSS-36B-Instruct
40/100- ECI—
- Price—
- Context524K
NVIDIALlama 3.3 Nemotron Super 49B v1.5
31/100- ECI—
- Price$0.40 / $0.40
- Context131K
Add a model
Make it a three-way comparison.
Seed-OSS-36B-Instruct is our pick
Seed-OSS-36B-Instruct is the better all-round choice, scoring 40/100 against Llama 3.3 Nemotron Super 49B v1.5 (31). It leads on context window. The score weighs inputs & features 60%, context window 40%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceLlama 3.3 Nemotron Super 49B v1.5Llama 3.3 Nemotron Super 49B v1.5 $0.40 per 1M tokens (3:1 blend) · Seed-OSS-36B-Instruct unpriced
- Longest contextSeed-OSS-36B-InstructSeed-OSS-36B-Instruct 524,288 · Llama 3.3 Nemotron Super 49B v1.5 131,072 tokens
- Widest inputsSame inputsSeed-OSS-36B-Instruct: Text · Llama 3.3 Nemotron Super 49B v1.5: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Seed-OSS-36B-Instruct | Llama 3.3 Nemotron Super 49B v1.5 |
|---|---|---|---|
| Inputs & features | 60% | 35 | 35 |
| Context window | 40% | 49 | 25 |
| Overall | 100% | 40/100 | 31/100 |
Left out because at least one model lacks the data: capability and price. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Seed-OSS-36B-InstructByteDance Seed | Llama 3.3 Nemotron Super 49B v1.5NVIDIA |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| GPQA DiamondGraduate-level science questions | 71.5% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 67.5% | — |
| Price per million tokens | ||
| Input | — | $0.40 |
| Output | — | $0.40 |
| Cached input | — | — |
| Blended (3:1) | — | $0.40 |
| Long-context rate | — | Same rate |
| Price source | — | Median of 1 providers |
| Limits | ||
| Context window | 524,288 tokens (best) | 131,072 tokens |
| Max output | 524,288 tokens (best) | 131,072 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yes | Yes |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | OpenApache 2.0 | Open |
| API model ID | — | — |
| API providers | — | 1 |
| Released | Aug 20, 2025 | Jul 25, 2025 |
| Knowledge cutoff | Jul 2024 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Seed-OSS-36B-Instruct—
- Llama 3.3 Nemotron Super 49B v1.5$4.80
Which should you choose?
Which is better: Seed-OSS-36B-Instruct or Llama 3.3 Nemotron Super 49B v1.5?
Seed-OSS-36B-Instruct is the better all-round choice, scoring 40/100 against Llama 3.3 Nemotron Super 49B v1.5 (31). It leads on context window. The score weighs inputs & features 60%, context window 40%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Seed-OSS-36B-Instruct or Llama 3.3 Nemotron Super 49B v1.5?
Llama 3.3 Nemotron Super 49B v1.5 is cheaper at $0.40 input / $0.40 output per million tokens (median across 1 API provider). . At a typical mix of three input tokens to one output token, that is $0.40 per million tokens for Llama 3.3 Nemotron Super 49B v1.5 versus . Seed-OSS-36B-Instruct has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Seed-OSS-36B-Instruct has not been scored yet and Llama 3.3 Nemotron Super 49B v1.5 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Seed-OSS-36B-Instruct and Llama 3.3 Nemotron Super 49B v1.5 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.
Which has the bigger context window?
Seed-OSS-36B-Instruct has the largest context window at 524,288 tokens, against 131,072 for Llama 3.3 Nemotron Super 49B v1.5. Maximum output per response: Seed-OSS-36B-Instruct up to 524,288, Llama 3.3 Nemotron Super 49B v1.5 up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Seed-OSS-36B-Instruct accepts text; Llama 3.3 Nemotron Super 49B v1.5 accepts text. They handle the same number of input types.
Are any of these open source?
Yes, both publish their weights (Apache 2.0), so you can self-host them.
Which is newer?
Seed-OSS-36B-Instruct is the newest, released Aug 20, 2025. Llama 3.3 Nemotron Super 49B v1.5 came out Jul 25, 2025. Knowledge cutoff: Seed-OSS-36B-Instruct Jul 2024.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Nov 2, 2026.
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