Llama 4 Maverick 17B Instruct vs Mistral Large 2.1 vs DeepSeek-V3
Llama 4 Maverick 17B Instruct comes out ahead, 57 to 49 and 38 on our weighted score, and it is the cheaper option too.
- Our pick
Meta
Llama 4 Maverick 17B Instruct
57/100- ECI132.3
- Price$0.245 / $0.838
- Context1M
Mistral AI
Mistral Large 2.1
38/100- ECI128.6
- Price$2.00 / $6.00
- Context131K
DeepSeek
DeepSeek-V3
49/100- 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 57/100 against DeepSeek-V3 (49) and Mistral Large 2.1 (38). It leads on price, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityLlama 4 Maverick 17B InstructCapabilities Index (ECI): Llama 4 Maverick 17B Instruct 132.3 · DeepSeek-V3 132.3 · Mistral Large 2.1 128.6
- Lowest priceLlama 4 Maverick 17B InstructLlama 4 Maverick 17B Instruct $0.393 · DeepSeek-V3 $0.515 · Mistral Large 2.1 $3.00 per 1M tokens (3:1 blend)
- Longest contextLlama 4 Maverick 17B InstructLlama 4 Maverick 17B Instruct 1,000,000 · Mistral Large 2.1 131,072 · DeepSeek-V3 131,072 tokens
- Widest inputsLlama 4 Maverick 17B InstructLlama 4 Maverick 17B Instruct: Text, Images · Mistral Large 2.1: 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 | Mistral Large 2.1 | DeepSeek-V3 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 55 | 50 | 55 |
| Price | 25% | 66 | 26 | 61 |
| Inputs & features | 15% | 50 | 25 | 25 |
| Context window | 10% | 60 | 25 | 25 |
| Overall | 100% | 57/100 | 38/100 | 49/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 132.3 (best) | 128.6 | 132.3 |
| ECI rank | #135 of 165 (best) | #142 of 165 | #136 of 165 |
| GPQA DiamondGraduate-level science questions | 67.0% (best) | 51.3% | 56.5% |
| OTIS Mock AIME 2024–2025Competition mathematics | 20.6% (best) | 7.8% | 15.8% |
| Price per million tokens | |||
| Input | $0.245 (best) | $2.00 | $0.32 |
| Output | $0.838 (best) | $6.00 | $1.10 |
| Cached input | — | — | — |
| Blended (3:1) | $0.393 (best) | $3.00 | $0.515 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 16 providers | Median of 2 providers | Median of 8 providers |
| Limits | |||
| Context window | 1,000,000 tokens (best) | 131,072 tokens | 131,072 tokens |
| Max output | 16,384 tokens (best) | 16,384 tokens (best) | 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 | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Open | OpenDeepSeek Model License |
| API model ID | — | — | — |
| API providers | 16 (best) | 2 | 8 |
| Released | Apr 5, 2025 | Nov 18, 2024 | Dec 26, 2024 |
| Knowledge cutoff | Aug 2024 | Nov 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$4.13
Mistral Large 2.1$32.00
DeepSeek-V3$5.40
Which should you choose?
Which is better: Llama 4 Maverick 17B Instruct, Mistral Large 2.1 or DeepSeek-V3?
Llama 4 Maverick 17B Instruct is the better all-round choice, scoring 57/100 against DeepSeek-V3 (49) and Mistral Large 2.1 (38). 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, Mistral Large 2.1 or DeepSeek-V3?
Llama 4 Maverick 17B Instruct is cheaper at $0.245 input / $0.838 output per million tokens (median across 16 API providers). DeepSeek-V3 costs $0.32 input / $1.10 output per million tokens (median across 8 API providers); Mistral Large 2.1 costs $2.00 input / $6.00 output per million tokens (median across 2 API providers). At a typical mix of three input tokens to one output token, that is $0.393 per million tokens for Llama 4 Maverick 17B Instruct versus $0.515 for DeepSeek-V3 (1.3× as much) and $3.00 for Mistral Large 2.1 (7.6× as much).
Which scores higher on benchmarks?
Llama 4 Maverick 17B Instruct scores higher on the Capabilities Index (ECI): Llama 4 Maverick 17B Instruct 132.3 (#135 of 165), DeepSeek-V3 132.3 (#136 of 165) and Mistral Large 2.1 128.6 (#142 of 165). The confidence ranges of the top two overlap (128.6–134.2 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%, Mistral Large 2.1 51.3%; OTIS Mock AIME 2024–2025 — Llama 4 Maverick 17B Instruct 20.6%, DeepSeek-V3 15.8%, Mistral Large 2.1 7.8%.
Which is better for coding?
There are no published SWE-bench Verified results for Llama 4 Maverick 17B Instruct, Mistral Large 2.1 and DeepSeek-V3 yet, so there is no like-for-like coding score. On overall capability, Llama 4 Maverick 17B Instruct 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 Mistral Large 2.1 and 131,072 for DeepSeek-V3. Maximum output per response: Llama 4 Maverick 17B Instruct up to 16,384, Mistral Large 2.1 up to 16,384, DeepSeek-V3 up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Llama 4 Maverick 17B Instruct accepts text and images; Mistral Large 2.1 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 (DeepSeek Model License), so you can self-host them.
Which is newer?
Llama 4 Maverick 17B Instruct is the newest, released Apr 5, 2025. DeepSeek-V3 came out Dec 26, 2024; Mistral Large 2.1 came out Nov 18, 2024. Knowledge cutoff: Llama 4 Maverick 17B Instruct Aug 2024, Mistral Large 2.1 Nov 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.