Codestral 25.08 vs Llama 3.3 Nemotron Super 49B v1.5 vs Seed 1.6 Vision
Seed 1.6 Vision comes out ahead, 61 to 48 and 47 on our weighted score, and it is the cheaper option too.
Mistral AICodestral 25.08
47/100- ECI—
- Price$0.30 / $0.90
- Context128K
NVIDIALlama 3.3 Nemotron Super 49B v1.5
48/100- ECI—
- Price$0.40 / $0.40
- Context131K
- Our pick
ByteDance SeedSeed 1.6 Vision
61/100- ECI—
- Price$0.119 / $1.19
- Context256K
Seed 1.6 Vision is our pick
Seed 1.6 Vision is the better all-round choice, scoring 61/100 against Llama 3.3 Nemotron Super 49B v1.5 (48) and Codestral 25.08 (47). It leads on inputs & features and context window. The score weighs price 50%, inputs & features 30%, context window 20%. 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 priceSeed 1.6 VisionSeed 1.6 Vision $0.386 · Llama 3.3 Nemotron Super 49B v1.5 $0.40 · Codestral 25.08 $0.45 per 1M tokens (3:1 blend)
- Longest contextSeed 1.6 VisionSeed 1.6 Vision 256,000 · Llama 3.3 Nemotron Super 49B v1.5 131,072 · Codestral 25.08 128,000 tokens
- Widest inputsSeed 1.6 VisionCodestral 25.08: Text · Llama 3.3 Nemotron Super 49B v1.5: Text · Seed 1.6 Vision: Text, Images
- Self-hostingLlama 3.3 Nemotron Super 49B v1.5Publishes downloadable weights
| Measure | Weight | Codestral 25.08 | Llama 3.3 Nemotron Super 49B v1.5 | Seed 1.6 Vision |
|---|---|---|---|---|
| Price | 50% | 64 | 66 | 67 |
| Inputs & features | 30% | 35 | 35 | 70 |
| Context window | 20% | 24 | 25 | 36 |
| Overall | 100% | 47/100 | 48/100 | 61/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Codestral 25.08Mistral AI | Llama 3.3 Nemotron Super 49B v1.5NVIDIA | Seed 1.6 VisionByteDance Seed |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.30 | $0.40 | $0.119 (best) |
| Output | $0.90 | $0.40 (best) | $1.19 |
| Cached input | $0.03 | — | $0.024 (best) |
| Blended (3:1) | $0.45 | $0.40 | $0.386 (best) |
| Long-context rate | Same rate | Same rate | Over 32K: $0.178 / $2.37 |
| Price source | Official Mistral API | Median of 1 providers | Official Volcengine Ark API |
| Limits | |||
| Context window | 128,000 tokens | 131,072 tokens | 256,000 tokens (best) |
| Max output | 8,192 tokens | 131,072 tokens (best) | 32,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | Yes |
| Availability | |||
| Weights | Proprietary | Open | Proprietary |
| API model ID | codestral-2508 | — | doubao-seed-1-6-vision-250815 |
| API providers | 11 (best) | 1 | 2 |
| Released | Jul 30, 2025 | Jul 25, 2025 | Aug 15, 2025 |
| Knowledge cutoff | — | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Codestral 25.08$4.80
- Llama 3.3 Nemotron Super 49B v1.5$4.80
- Seed 1.6 Vision$3.56
Which should you choose?
Which is better: Codestral 25.08, Llama 3.3 Nemotron Super 49B v1.5 or Seed 1.6 Vision?
Seed 1.6 Vision is the better all-round choice, scoring 61/100 against Llama 3.3 Nemotron Super 49B v1.5 (48) and Codestral 25.08 (47). It leads on inputs & features and context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Codestral 25.08, Llama 3.3 Nemotron Super 49B v1.5 or Seed 1.6 Vision?
Seed 1.6 Vision is cheaper at $0.119 input / $1.19 output per million tokens (official Volcengine Ark API price). Llama 3.3 Nemotron Super 49B v1.5 costs $0.40 input / $0.40 output per million tokens (median across 1 API provider); Codestral 25.08 costs $0.30 input / $0.90 output per million tokens (official Mistral API price). At a typical mix of three input tokens to one output token, that is $0.386 per million tokens for Seed 1.6 Vision versus $0.40 for Llama 3.3 Nemotron Super 49B v1.5 (1× as much) and $0.45 for Codestral 25.08 (1.2× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Codestral 25.08 has not been scored yet, Llama 3.3 Nemotron Super 49B v1.5 has not been scored yet and Seed 1.6 Vision has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Codestral 25.08, Llama 3.3 Nemotron Super 49B v1.5 and Seed 1.6 Vision yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
Seed 1.6 Vision has the largest context window at 256,000 tokens, against 131,072 for Llama 3.3 Nemotron Super 49B v1.5 and 128,000 for Codestral 25.08. Maximum output per response: Codestral 25.08 up to 8,192, Llama 3.3 Nemotron Super 49B v1.5 up to 131,072, Seed 1.6 Vision up to 32,000 tokens.
Which can read images, PDFs, audio or video?
Codestral 25.08 accepts text; Llama 3.3 Nemotron Super 49B v1.5 accepts text; Seed 1.6 Vision accepts text and images. Seed 1.6 Vision handles the widest range of inputs.
Are any of these open source?
Llama 3.3 Nemotron Super 49B v1.5 publishes its weights and can be self-hosted; Codestral 25.08 and Seed 1.6 Vision is proprietary.
Which is newer?
Seed 1.6 Vision is the newest, released Aug 15, 2025. Codestral 25.08 came out Jul 30, 2025; Llama 3.3 Nemotron Super 49B v1.5 came out Jul 25, 2025.
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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