MiniMax-Text 7B: pricing, context window and benchmarks
MiniMax-Text 7B is a small open-weight model from MiniMax. It offers a 16,384-token context window, costs $1.10 per million input tokens and $4.16 per million output tokens, and averages 57.7 across the index's benchmark suite.
Pricing
MiniMax-Text 7B costs $1.10 per million input tokens and $4.16 per million output tokens. A blended 3:1 input-to-output mix works out to about $1.87 per million tokens. Cached input is listed at $0.17 per million tokens.
| Item | Price | Notes |
|---|---|---|
| Input | $1.10 | per 1M tokens |
| Output | $4.16 | per 1M tokens |
| Cached input | $0.17 | per 1M tokens |
| Blended 3:1 | $1.87 | estimate per 1M tokens |
| 1M in + 1M out | $5.26 | estimate |
Benchmarks
Scores below are modelled estimates on a 0–100 scale. Use them to compare relative position, not as official vendor results.
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 63.0 | 489 | 19th | |
| GPQA Diamond | 54.6 | 471 | 22th | |
| SWE-bench Verified | 42.7 | 494 | 18th | |
| HumanEval | 60.2 | 503 | 16th | |
| MATH-500 | 59.9 | 467 | 22th | |
| AIME 2025 | 48.5 | 466 | 22th | |
| LiveCodeBench | 47.6 | 470 | 22th | |
| IFEval | 68.0 | 489 | 19th | |
| TruthfulQA | 63.0 | 493 | 18th | |
| HellaSwag | 73.6 | 463 | 23th | |
| MMMU | 53.4 | 515 | 14th | |
| Arena Elo | 1253.5 | 484 | 19th |
What MiniMax-Text 7B is good for
MiniMax-Text 7B is a small model. That makes it a good fit for classification, extraction, routing, summarization and other high-volume jobs where latency and cost dominate. It is not the right pick for open-ended frontier reasoning, but at $1.10 per million input tokens it can handle a large share of production traffic.
Strengths
- Input price of $1.10 per million tokens is at or below the index median.
- Open weights make self-hosting, fine-tuning and data-residency review possible.
Trade-offs
- Context window of 16,384 tokens is small for long-document work.
- Average benchmark score is below the index median; test it on your own task.
- Less reliable on open-ended reasoning and complex multi-step instructions.
How it compares
| Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|
| Nemotron 4 8B | NVIDIA | 4096 | $1.06 | 57.9 |
| Llama 3.3 7B | Meta AI | 8192 | $1.18 | 57.8 |
| Command R+ 8B | Cohere | 8192 | $1.21 | 57.7 |
| Hunyuan-Large 7B | Tencent | 32768 | $1.08 | 57.7 |
| MiniMax-Text 7B | MiniMax | 16384 | $1.10 | 57.7 |
| Llama 3.1 7B | Meta AI | 8192 | $1.01 | 57.4 |
FAQ
How much does MiniMax-Text 7B cost?
MiniMax-Text 7B is listed at $1.10 per million input tokens and $4.16 per million output tokens. Cached input is $0.17 per million tokens. A blended 3:1 input-to-output mix is about $1.87 per million tokens.
What is the context window of MiniMax-Text 7B?
MiniMax-Text 7B has a context window of 16,384 tokens and can emit up to 8,192 output tokens per request in this index.
Is MiniMax-Text 7B open weights?
Yes. MiniMax-Text 7B is listed as an open-weight model under a open weights licence.
How does MiniMax-Text 7B score on benchmarks?
MiniMax-Text 7B averages 57.7 across the scored benchmarks in this index, ranking #478 of 600 models. Its strongest relative result is Arena Elo at 1253.5.
What is MiniMax-Text 7B best for?
MiniMax-Text 7B is a small model. That makes it a good fit for classification, extraction, routing, summarization and other high-volume jobs where latency and cost dominate. It is not the right pick for open-ended frontier reasoning, but at $1.10 per million input tokens it can handle a large share of production traffic.