MiniMax M1 80K vs Morph V3 Fast vs Qwen2.5-VL 72B Instruct
Too close to call on our weighted score (MiniMax M1 80K 47, Qwen2.5-VL 72B Instruct 44, Morph V3 Fast 32). The right pick depends on what you value most.
MiniMaxMiniMax M1 80K
47/100- ECI—
- Price$0.55 / $2.20
- Context1M
Morph
Morph V3 Fast
32/100- ECI—
- Price$0.80 / $1.20
- Context262K
Alibaba (Qwen)Qwen2.5-VL 72B Instruct
44/100- ECI—
- Price$0.905 / $1.00
- Context131K
Too close to call
It is close. Our weighted score puts them within 2 points (MiniMax M1 80K 47/100, Qwen2.5-VL 72B Instruct 44/100, Morph V3 Fast 32/100), so choose by what matters most for your work: Morph V3 Fast on price and MiniMax M1 80K for long inputs. 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 priceMorph V3 FastMorph V3 Fast $0.90 · Qwen2.5-VL 72B Instruct $0.93 · MiniMax M1 80K $0.963 per 1M tokens (3:1 blend)
- Longest contextMiniMax M1 80KMiniMax M1 80K 1,000,000 · Morph V3 Fast 262,144 · Qwen2.5-VL 72B Instruct 131,072 tokens
- Widest inputsQwen2.5-VL 72B InstructMiniMax M1 80K: Text · Morph V3 Fast: Text · Qwen2.5-VL 72B Instruct: Text, Images
- Self-hostingMiniMax M1 80K and Qwen2.5-VL 72B InstructPublishes downloadable weights (Apache-2.0)
| Measure | Weight | MiniMax M1 80K | Morph V3 Fast | Qwen2.5-VL 72B Instruct |
|---|---|---|---|---|
| Price | 50% | 48 | 50 | 49 |
| Inputs & features | 30% | 35 | 0 | 50 |
| Context window | 20% | 60 | 37 | 25 |
| Overall | 100% | 47/100 | 32/100 | 44/100 |
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 | MiniMax M1 80KMiniMax | Morph V3 FastMorph | Qwen2.5-VL 72B InstructAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.55 (best) | $0.80 | $0.905 |
| Output | $2.20 | $1.20 | $1.00 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.963 | $0.90 (best) | $0.93 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 5 providers | Median of 5 providers | Median of 6 providers |
| Limits | |||
| Context window | 1,000,000 tokens (best) | 262,144 tokens | 131,072 tokens |
| Max output | 80,000 tokens | 131,072 tokens (best) | 8,192 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 | Yes | No | No |
| Tool calling | Yes | No | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | OpenApache-2.0 | Proprietary | Open |
| API model ID | — | — | — |
| API providers | 5 | 5 | 6 (best) |
| Released | Jun 17, 2025 | Jul 7, 2025 | Jan 26, 2025 |
| Knowledge cutoff | — | — | Apr 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 M1 80K$9.90
- Morph V3 Fast$10.40
- Qwen2.5-VL 72B Instruct$11.06
Which should you choose?
Which is better: MiniMax M1 80K, Morph V3 Fast or Qwen2.5-VL 72B Instruct?
It is close. Our weighted score puts them within 2 points (MiniMax M1 80K 47/100, Qwen2.5-VL 72B Instruct 44/100, Morph V3 Fast 32/100), so choose by what matters most for your work: Morph V3 Fast on price and MiniMax M1 80K for long inputs. 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, MiniMax M1 80K, Morph V3 Fast or Qwen2.5-VL 72B Instruct?
Morph V3 Fast is cheaper at $0.80 input / $1.20 output per million tokens (median across 5 API providers). Qwen2.5-VL 72B Instruct costs $0.905 input / $1.00 output per million tokens (median across 6 API providers); MiniMax M1 80K costs $0.55 input / $2.20 output per million tokens (median across 5 API providers). At a typical mix of three input tokens to one output token, that is $0.90 per million tokens for Morph V3 Fast versus $0.93 for Qwen2.5-VL 72B Instruct (1× as much) and $0.963 for MiniMax M1 80K (1.1× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. MiniMax M1 80K has not been scored yet, Morph V3 Fast has not been scored yet and Qwen2.5-VL 72B Instruct has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for MiniMax M1 80K, Morph V3 Fast and Qwen2.5-VL 72B Instruct yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Morph V3 Fast does not support tool calling, which most coding agents need.
Which has the bigger context window?
MiniMax M1 80K has the largest context window at 1,000,000 tokens, against 262,144 for Morph V3 Fast and 131,072 for Qwen2.5-VL 72B Instruct. Maximum output per response: MiniMax M1 80K up to 80,000, Morph V3 Fast up to 131,072, Qwen2.5-VL 72B Instruct up to 8,192 tokens.
Which can read images, PDFs, audio or video?
MiniMax M1 80K accepts text; Morph V3 Fast accepts text; Qwen2.5-VL 72B Instruct accepts text and images. Qwen2.5-VL 72B Instruct handles the widest range of inputs.
Are any of these open source?
MiniMax M1 80K and Qwen2.5-VL 72B Instruct publishes its weights (Apache-2.0) and can be self-hosted; Morph V3 Fast is proprietary.
Which is newer?
Morph V3 Fast is the newest, released Jul 7, 2025. MiniMax M1 80K came out Jun 17, 2025; Qwen2.5-VL 72B Instruct came out Jan 26, 2025. Knowledge cutoff: Qwen2.5-VL 72B Instruct Apr 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.
