MiniMax-M2.5 vs Llama 4 Scout 17B Instruct
Too close to call on our weighted score (Llama 4 Scout 17B Instruct 62, MiniMax-M2.5 61). The right pick depends on what you value most.
MiniMax
MiniMax-M2.5
61/100- ECI146.7
- Price$0.30 / $1.20
- Context205K
Meta
Llama 4 Scout 17B Instruct
62/100- ECI129.7
- Price$0.225 / $0.69
- Context10M
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Too close to call
It is close. Our weighted score puts them within a point (Llama 4 Scout 17B Instruct 62/100, MiniMax-M2.5 61/100), so choose by what matters most for your work: MiniMax-M2.5 for raw capability, Llama 4 Scout 17B Instruct on price and Llama 4 Scout 17B Instruct for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityMiniMax-M2.5Capabilities Index (ECI): MiniMax-M2.5 146.7 · Llama 4 Scout 17B Instruct 129.7
- Lowest priceLlama 4 Scout 17B InstructLlama 4 Scout 17B Instruct $0.341 · MiniMax-M2.5 $0.525 per 1M tokens (3:1 blend)
- Longest contextLlama 4 Scout 17B InstructLlama 4 Scout 17B Instruct 10,000,000 · MiniMax-M2.5 204,800 tokens
- Widest inputsLlama 4 Scout 17B InstructMiniMax-M2.5: Text · Llama 4 Scout 17B Instruct: Text, Images
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | MiniMax-M2.5 | Llama 4 Scout 17B Instruct |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 74 | 52 |
| Price | 25% | 63 | 72 |
| Inputs & features | 15% | 35 | 50 |
| Context window | 10% | 32 | 100 |
| Overall | 100% | 61/100 | 62/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | ||
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 146.7 (best) | 129.7 |
| ECI rank | #66 of 148 (best) | #126 of 148 |
| GPQA DiamondGraduate-level science questions | — | 51.8% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 7.8% |
| Price per million tokens | ||
| Input | $0.30 | $0.225 (best) |
| Output | $1.20 | $0.69 (best) |
| Cached input | $0.03 | — |
| Blended (3:1) | $0.525 | $0.341 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Official MiniMax (minimax.io) API | Median of 4 providers |
| Limits | ||
| Context window | 204,800 tokens | 10,000,000 tokens (best) |
| Max output | 131,072 tokens (best) | 16,384 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | Yes |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yes | No |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Open | Open |
| API model ID | MiniMax-M2.5 | — |
| API providers | 21 (best) | 4 |
| Released | Feb 12, 2026 | Apr 5, 2025 |
| 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.
MiniMax-M2.5$5.40
Llama 4 Scout 17B Instruct$3.63
Which should you choose?
Which is better: MiniMax-M2.5 or Llama 4 Scout 17B Instruct?
It is close. Our weighted score puts them within a point (Llama 4 Scout 17B Instruct 62/100, MiniMax-M2.5 61/100), so choose by what matters most for your work: MiniMax-M2.5 for raw capability, Llama 4 Scout 17B Instruct on price and Llama 4 Scout 17B Instruct for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, MiniMax-M2.5 or Llama 4 Scout 17B Instruct?
Llama 4 Scout 17B Instruct is cheaper at $0.225 input / $0.69 output per million tokens (median across 4 API providers). MiniMax-M2.5 costs $0.30 input / $1.20 output per million tokens (official MiniMax (minimax.io) API price). At a typical mix of three input tokens to one output token, that is $0.341 per million tokens for Llama 4 Scout 17B Instruct versus $0.525 for MiniMax-M2.5 (1.5× as much).
Which scores higher on benchmarks?
MiniMax-M2.5 scores higher on the Capabilities Index (ECI): MiniMax-M2.5 146.7 (#66 of 148) and Llama 4 Scout 17B Instruct 129.7 (#126 of 148). Their confidence ranges do not overlap (142.3–147.9 vs 124.8–131.4), so the gap is a real one.
Which is better for coding?
There are no published SWE-bench Verified results for MiniMax-M2.5 and Llama 4 Scout 17B Instruct yet, so there is no like-for-like coding score. On overall capability, MiniMax-M2.5 leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.
Which has the bigger context window?
Llama 4 Scout 17B Instruct has the largest context window at 10,000,000 tokens, against 204,800 for MiniMax-M2.5. Maximum output per response: MiniMax-M2.5 up to 131,072, Llama 4 Scout 17B Instruct up to 16,384 tokens.
Which can read images, PDFs, audio or video?
MiniMax-M2.5 accepts text; Llama 4 Scout 17B Instruct accepts text and images. Llama 4 Scout 17B Instruct handles the widest range of inputs.
Are any of these open source?
Yes, both publish their weights, so you can self-host them.
Which is newer?
MiniMax-M2.5 is the newest, released Feb 12, 2026. Llama 4 Scout 17B Instruct came out Apr 5, 2025. Knowledge cutoff: Llama 4 Scout 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.