Claude 4.1 Opus vs MiniMax-M2
Head-to-head specifications
| Metric | Claude 4.1 Opus | MiniMax-M2 | Difference |
|---|---|---|---|
| Intelligence Index | 30.0 | 30.0 | — |
| Context window | 262K tokens | 262K tokens | — |
| Blended price ($/1M tokens) | $1.68 | $0.36 | +366.7% |
| Output speed (tokens/s) | 30 | 77 | -61.0% |
| Access | Proprietary API | Open weights | — |
- Claude 4.1 Opus leads overall capability (Intelligence Index 30.0 vs 30.0).
- MiniMax-M2 is the cheaper model to run at $0.36/1M blended tokens — about 4.7× cheaper.
Verdict: Claude 4.1 Opus or MiniMax-M2?
Claude 4.1 Opus advantages
- No decisive advantage on the tracked metrics.
MiniMax-M2 advantages
- Affordability (+79%)
- Output speed (+61%)
Which should you choose?
- Choose the MiniMax-M2 if you want the lowest cost per token at scale.
Value for money
MiniMax-M2 offers more intelligence per dollar (4.7× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use. It is also open-weight, so self-hosting can reduce costs further at scale.
Claude 4.1 Opus vs MiniMax-M2: which should you choose?
Claude 4.1 Opus — Anthropic multimodal model with an Intelligence Index of 30, a 262K-token context window and a blended price of $1.68/1M tokens.
MiniMax-M2 — MiniMax multimodal model with an Intelligence Index of 30, a 262K-token context window and a blended price of $0.36/1M tokens (open weights).
Claude 4.1 Opus vs MiniMax-M2: Claude 4.1 Opus scores higher on the Intelligence Index. Claude 4.1 Opus leads overall capability (Intelligence Index 30.0 vs 30.0). MiniMax-M2 is the cheaper model to run at $0.36/1M blended tokens — about 4.7× cheaper.
Capability: intelligence, coding and agentic work
On the composite Intelligence Index the Claude 4.1 Opus scores 30.0 versus 30.0. Composite indices summarize many evaluations, but always test on your own workload before committing.
Context window and speed
The Claude 4.1 Opus accepts up to 262K tokens per request, which sets how much documentation, transcript or code it can reason over at once. In measured throughput, MiniMax-M2 generates faster (77 vs 30 tokens/s), which matters for interactive apps and high-volume pipelines.
Pricing and access
At blended per-token rates, MiniMax-M2 is the cheaper model to run ($0.36 vs $1.68 per 1M tokens). Claude 4.1 Opus is proprietary api and MiniMax-M2 is open weights. Open-weight models can be self-hosted, trading per-call cost for infrastructure you manage; for production also weigh rate limits, throughput and data-residency requirements.
The verdict
Both are credible choices in the ai model comparison space; the specification table above lays out every metric so you can weigh the trade-offs that matter to you. Pick the one whose strengths line up with how you will actually use it.
Frequently asked questions
Is the Claude 4.1 Opus better than the MiniMax-M2?
MiniMax-M2 is the clearly stronger overall choice, winning most of the dimensions that matter. Claude 4.1 Opus leads overall capability (Intelligence Index 30.0 vs 30.0).
What is the main difference between the Claude 4.1 Opus and the MiniMax-M2?
Claude 4.1 Opus leads overall capability (Intelligence Index 30.0 vs 30.0). MiniMax-M2 is the cheaper model to run at $0.36/1M blended tokens — about 4.7× cheaper.
Which is better value?
MiniMax-M2 offers more intelligence per dollar (4.7× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use. It is also open-weight, so self-hosting can reduce costs further at scale.
Which should I choose?
Choose the MiniMax-M2 if you want the lowest cost per token at scale.
Methodology
Large language models are compared on independent leaderboard metrics: an Intelligence Index (a composite of reasoning and knowledge evaluations), Coding and Agentic indices where measured, community arena Elo, maximum context window, a blended API price per million tokens (weighted across cache-hit, input and output rates), and measured output speed in tokens per second. Where a model ships multiple reasoning-effort variants, we report its strongest variant. Benchmarks capture only part of real-world quality, which also depends on tool use, latency, safety and task fit — and this space moves quickly, so figures reflect the leaderboard snapshot on the page date.