minimax-m2.1
OpenRouter · chat model
minimax-m2.1 is listed here as a chat model from OpenRouter. This page shows simple API pricing, token limits, and capability flags so you can compare it with similar options.
Input
$0.2700 / 1M tokens
Output
$1.2000 / 1M tokens
Cached input
N/A
0 in raw data; semantics unverified
Context
64.0K
Quick read
Best for
Use this page when you need a fast view of cost, context size, and supported features before testing the model in your own workload.
Things to verify
Always check the provider page for discounts, cache pricing, region rules, and any model limits that may not appear in public metadata.
Pricing
| Item | Price |
|---|---|
| Input | $0.2700 / 1M tokens |
| Output | $1.2000 / 1M tokens |
| Cached input | N/A 0 in raw data; semantics unverified |
| Cache write | N/A 0 in raw data; semantics unverified |
| Embedding | $0.2700 / 1M tokens |
Token limits
Context window
64.0K
Max input tokens
204.0K
Max output tokens
64.0K
Max tokens
64.0K
Capabilities
| Capability | Supported |
|---|---|
| Vision | ✅ |
| Function calling | ✅ |
| Parallel function calling | — |
| Tool choice | ✅ |
| Prompt caching | — |
| Reasoning | ✅ |
| Response schema | — |
| System messages | — |
| Audio input | — |
| Audio output | — |
| Web search | — |
| PDF input | — |
| Video input | — |
Benchmarks
Most benchmark rows are attached to the base model family rather than this provider route. Open benchmark explorer
| Benchmark | Score | Metric | Scope | Checked | Source |
|---|---|---|---|---|---|
| SWE-bench Verified | 69.4 | score | Base model: MiniMax-M2 (MiniMax-M2) | 2026-05-31 | Link |
| Multi-SWE-bench | 36.2 | score | Base model: MiniMax-M2 (MiniMax-M2) | 2026-05-31 | Link |
| SWE-bench Multilingual | 56.5 | score | Base model: MiniMax-M2 (MiniMax-M2) | 2026-05-31 | Link |
| Terminal-Bench | 46.3 | score | Base model: MiniMax-M2 (MiniMax-M2) | 2026-05-31 | Link |
| ArtifactsBench | 66.8 | score | Base model: MiniMax-M2 (MiniMax-M2) | 2026-05-31 | Link |
| BrowseComp | 44 | score | Base model: MiniMax-M2 (MiniMax-M2) | 2026-05-31 | Link |
| SWE-bench Verified | 74.0 | score | Base model: MiniMax-M2.1 (MiniMax-M2.1) | 2026-05-31 | Link |
| Multi-SWE-bench | 49.4 | score | Base model: MiniMax-M2.1 (MiniMax-M2.1) | 2026-05-31 | Link |
| SWE-bench Multilingual | 72.5 | score | Base model: MiniMax-M2.1 (MiniMax-M2.1) | 2026-05-31 | Link |
| Terminal-Bench 2.0 | 47.9 | score | Base model: MiniMax-M2.1 (MiniMax-M2.1) | 2026-05-31 | Link |
| VIBE (Average) | 88.6 | score | Base model: MiniMax-M2.1 (MiniMax-M2.1) | 2026-05-31 | Link |
| VIBE-Web | 91.5 | score | Base model: MiniMax-M2.1 (MiniMax-M2.1) | 2026-05-31 | Link |
| VIBE-Android | 89.7 | score | Base model: MiniMax-M2.1 (MiniMax-M2.1) | 2026-05-31 | Link |
Sources
| Source links | |
| Pricing data | LiteLLM model cost map |
| Synced at | 2026-05-28 |
Docs
| Official docs |
Similar models
This list is ranked by overall similarity. Use filters to emphasize the lens that matters most for the replacement you are making.
Comparing from
| Model | Cost | Input shape | Features | Context | Why it is close |
|---|---|---|---|---|---|
| minimax-m2.1 OpenRouter | In $0.2700 / 1M tokens Out $1.2000 / 1M tokens | text
Output: text | VisionFunction callingTool choiceReasoning | 64.0K | Current model Reference row |
| Model | Cost | Input shape | Features | Context | Why it is close |
|---|---|---|---|---|---|
| glm-4.7 OpenRouter | In $0.4000 / 1M tokens Out $1.5000 / 1M tokens | text
Output: text | VisionFunction callingTool choiceReasoning | 64.0K | Same provider Overall 95% |
| qwen.qwen3-coder-480b-a35b-v1:0 bedrock_converse | In $0.2200 / 1M tokens Out $1.8000 / 1M tokens | text
Output: text | Function callingTool choiceReasoning | 65.5K | Text covered Overall 88% |
| minimax-m2.5 OpenRouter | In $0.3000 / 1M tokens Out $1.1000 / 1M tokens | text
Output: text | Function callingTool choiceReasoning | 65.5K | Same provider Overall 88% |
| DeepSeek-V3.1 deepinfra | In $0.2700 / 1M tokens Out $1.0000 / 1M tokens | text
Output: text | Function callingTool choiceReasoning | 163.8K | Text covered Overall 83% |
| deepseek.v3-v1:0 bedrock_converse | In $0.5800 / 1M tokens Out $1.6800 / 1M tokens | text
Output: text | Function callingTool choiceReasoning | 81.9K | Text covered Overall 83% |
| qwen.qwen3-235b-a22b-2507-v1:0 bedrock_converse | In $0.2200 / 1M tokens Out $0.8800 / 1M tokens | text
Output: text | Function callingTool choiceReasoning | 131.1K | Text covered Overall 81% |
| qwen3.5-35b-a3b OpenRouter | In $0.2500 / 1M tokens Out $2.0000 / 1M tokens | text imagevideo
Output: text | VisionFunction callingTool choiceReasoning | 65.5K | Same provider Overall 79% |
| glm-4.7-flash OpenRouter | In $0.0700 / 1M tokens Out $0.4000 / 1M tokens | text
Output: text | VisionFunction callingTool choiceReasoning | 32.0K | Same provider Overall 79% |
| qwen3-coder-plus OpenRouter | In $1.0000 / 1M tokens Out $5.0000 / 1M tokens | text
Output: text | Function callingTool choiceReasoning | 65.5K | Same provider Overall 78% |
| qwen3.6-plus OpenRouter | In $0.3250 / 1M tokens Out $1.9500 / 1M tokens | text imagevideo
Output: text | VisionFunction callingTool choiceReasoning | 65.5K | Same provider Overall 78% |
| qwen3.5-27b OpenRouter | In $0.3000 / 1M tokens Out $2.4000 / 1M tokens | text imagevideo
Output: text | VisionFunction callingTool choiceReasoning | 65.5K | Same provider Overall 77% |
| qwen3.5-122b-a10b OpenRouter | In $0.4000 / 1M tokens Out $2.0000 / 1M tokens | text imagevideo
Output: text | VisionFunction callingTool choiceReasoning | 65.5K | Same provider Overall 76% |
| minimax.minimax-m2.5 Bedrock | In $0.3000 / 1M tokens Out $1.2000 / 1M tokens | text
Output: text | Function callingTool choiceReasoning | 8.2K | Text covered Overall 76% |
| Qwen3-Coder-480B-A35B-Instruct-Turbo deepinfra | In $0.2900 / 1M tokens Out $1.2000 / 1M tokens | text
Output: text | Function callingTool choice | 262.1K | Text covered Overall 76% |
| qwen3.5-plus-02-15 OpenRouter | In $0.4000 / 1M tokens Out $2.4000 / 1M tokens | text imagevideo
Output: text | VisionFunction callingTool choiceReasoning | 65.5K | Same provider Overall 75% |
| deepseek.v3.2 Bedrock | In $0.7400 / 1M tokens Out $2.2200 / 1M tokens | text
Output: text | Function callingTool choiceReasoning | 163.8K | Text covered Overall 74% |
| deepseek.v3.2 Bedrock | In $0.7400 / 1M tokens Out $2.2200 / 1M tokens | text
Output: text | Function callingTool choiceReasoning | 163.8K | Text covered Overall 74% |
| deepseek.v3.2 Bedrock | In $0.7400 / 1M tokens Out $2.2200 / 1M tokens | text
Output: text | Function callingTool choiceReasoning | 163.8K | Text covered Overall 74% |
| minimax.minimax-m2.1 Bedrock | In $0.3000 / 1M tokens Out $1.2000 / 1M tokens | text
Output: text | Function callingTool choice | 8.2K | Text covered Overall 71% |
| minimax.minimax-m2.5 Bedrock | In $0.3000 / 1M tokens Out $1.2000 / 1M tokens | text
Output: text | Function callingTool choice | 8.2K | Text covered Overall 71% |
| minimax.minimax-m2.1 Bedrock | In $0.3000 / 1M tokens Out $1.2000 / 1M tokens | text
Output: text | Function callingTool choice | 8.2K | Text covered Overall 71% |
| minimax.minimax-m2.1 Bedrock | In $0.3000 / 1M tokens Out $1.2000 / 1M tokens | text
Output: text | Function callingTool choice | 8.2K | Text covered Overall 71% |
| Phi-4-reasoning azure_ai | In $0.1250 / 1M tokens Out $0.5000 / 1M tokens | text
Output: text | Function callingTool choiceReasoning | 4.1K | Text covered Overall 68% |
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