Llama 4 Maverick 17B Instruct vs Magistral Small vs DeepSeek-V3
Llama 4 Maverick 17B Instruct comes out ahead, 58 to 50 and 50 on our weighted score, and it is the cheaper option too.
- Our pick
Meta
Llama 4 Maverick 17B Instruct
58/100- ECI132.2
- Price$0.321 / $0.91
- Context1M
Mistral AI
Magistral Small
50/100- ECI133.2
- Price$0.50 / $1.50
- Context131K
DeepSeek
DeepSeek-V3
50/100- ECI132.3
- Price$0.32 / $1.10
- Context131K
Llama 4 Maverick 17B Instruct is our pick
Llama 4 Maverick 17B Instruct is the better all-round choice, scoring 58/100 against Magistral Small (50) and DeepSeek-V3 (50). It leads on price, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityMagistral SmallCapabilities Index (ECI): Magistral Small 133.2 · DeepSeek-V3 132.3 · Llama 4 Maverick 17B Instruct 132.2
- Lowest priceLlama 4 Maverick 17B InstructLlama 4 Maverick 17B Instruct $0.468 · DeepSeek-V3 $0.515 · Magistral Small $0.75 per 1M tokens (3:1 blend)
- Longest contextLlama 4 Maverick 17B InstructLlama 4 Maverick 17B Instruct 1,000,000 · Magistral Small 131,072 · DeepSeek-V3 131,072 tokens
- Widest inputsLlama 4 Maverick 17B InstructLlama 4 Maverick 17B Instruct: Text, Images · Magistral Small: Text · DeepSeek-V3: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Llama 4 Maverick 17B Instruct | Magistral Small | DeepSeek-V3 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 56 | 57 | 56 |
| Price | 25% | 66 | 56 | 64 |
| Inputs & features | 15% | 50 | 35 | 25 |
| Context window | 10% | 60 | 24 | 24 |
| Overall | 100% | 58/100 | 50/100 | 50/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 132.2 | 133.2 (best) | 132.3 |
| ECI rank | #122 of 148 | #120 of 148 (best) | #121 of 148 |
| GPQA DiamondGraduate-level science questions | 67.0% (best) | 56.1% | 56.5% |
| OTIS Mock AIME 2024–2025Competition mathematics | 20.6% | 30.0% (best) | 15.8% |
| Price per million tokens | |||
| Input | $0.321 | $0.50 | $0.32 (best) |
| Output | $0.91 (best) | $1.50 | $1.10 |
| Cached input | — | — | — |
| Blended (3:1) | $0.468 (best) | $0.75 | $0.515 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 6 providers | Median of 1 providers | Median of 5 providers |
| Limits | |||
| Context window | 1,000,000 tokens (best) | 131,072 tokens | 131,072 tokens |
| Max output | 16,384 tokens (best) | 8,192 tokens | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | Yes | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | OpenApache 2.0 | OpenDeepSeek Model License |
| API model ID | — | — | — |
| API providers | 6 (best) | 1 | 5 |
| Released | Apr 5, 2025 | Jun 10, 2025 | Dec 26, 2024 |
| Knowledge cutoff | Aug 2024 | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
Llama 4 Maverick 17B Instruct$5.03
Magistral Small$8.00
DeepSeek-V3$5.40
Which should you choose?
Which is better: Llama 4 Maverick 17B Instruct, Magistral Small or DeepSeek-V3?
Llama 4 Maverick 17B Instruct is the better all-round choice, scoring 58/100 against Magistral Small (50) and DeepSeek-V3 (50). It leads on price, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Llama 4 Maverick 17B Instruct, Magistral Small or DeepSeek-V3?
Llama 4 Maverick 17B Instruct is cheaper at $0.321 input / $0.91 output per million tokens (median across 6 API providers). DeepSeek-V3 costs $0.32 input / $1.10 output per million tokens (median across 5 API providers); Magistral Small costs $0.50 input / $1.50 output per million tokens (median across 1 API provider). At a typical mix of three input tokens to one output token, that is $0.468 per million tokens for Llama 4 Maverick 17B Instruct versus $0.515 for DeepSeek-V3 (1.1× as much) and $0.75 for Magistral Small (1.6× as much).
Which scores higher on benchmarks?
Magistral Small scores higher on the Capabilities Index (ECI): Magistral Small 133.2 (#120 of 148), DeepSeek-V3 132.3 (#121 of 148) and Llama 4 Maverick 17B Instruct 132.2 (#122 of 148). The confidence ranges of the top two overlap (128.9–134.4 vs 127.5–135.5), so treat the gap as small. On individual benchmarks: GPQA Diamond — Llama 4 Maverick 17B Instruct 67.0%, DeepSeek-V3 56.5%, Magistral Small 56.1%; OTIS Mock AIME 2024–2025 — Magistral Small 30.0%, Llama 4 Maverick 17B Instruct 20.6%, DeepSeek-V3 15.8%.
Which is better for coding?
There are no published SWE-bench Verified results for Llama 4 Maverick 17B Instruct, Magistral Small and DeepSeek-V3 yet, so there is no like-for-like coding score. On overall capability, Magistral Small leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.
Which has the bigger context window?
Llama 4 Maverick 17B Instruct has the largest context window at 1,000,000 tokens, against 131,072 for Magistral Small and 131,072 for DeepSeek-V3. Maximum output per response: Llama 4 Maverick 17B Instruct up to 16,384, Magistral Small up to 8,192, DeepSeek-V3 up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Llama 4 Maverick 17B Instruct accepts text and images; Magistral Small accepts text; DeepSeek-V3 accepts text. Llama 4 Maverick 17B Instruct handles the widest range of inputs.
Are any of these open source?
Yes, all three publish their weights (Apache 2.0 and DeepSeek Model License), so you can self-host them.
Which is newer?
Magistral Small is the newest, released Jun 10, 2025. Llama 4 Maverick 17B Instruct came out Apr 5, 2025; DeepSeek-V3 came out Dec 26, 2024. Knowledge cutoff: Llama 4 Maverick 17B Instruct Aug 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 Oct 4, 2026.