MiniMax-Text 1.5B: pricing, context window and benchmarks
MiniMax-Text 1.5B is a small open-weight model from MiniMax. It offers a 32,768-token context window, costs $0.58 per million input tokens and $2.90 per million output tokens, and averages 51.5 across the index's benchmark suite.
Pricing
MiniMax-Text 1.5B costs $0.58 per million input tokens and $2.90 per million output tokens. A blended 3:1 input-to-output mix works out to about $1.16 per million tokens. Cached input is listed at $0.06 per million tokens.
| Item | Price | Notes |
|---|---|---|
| Input | $0.58 | per 1M tokens |
| Output | $2.90 | per 1M tokens |
| Cached input | $0.06 | per 1M tokens |
| Blended 3:1 | $1.16 | estimate per 1M tokens |
| 1M in + 1M out | $3.48 | 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 | 58.0 | 550 | 8th | |
| GPQA Diamond | 46.5 | 553 | 8th | |
| SWE-bench Verified | 36.1 | 546 | 9th | |
| HumanEval | 54.1 | 548 | 9th | |
| MATH-500 | 54.0 | 527 | 12th | |
| AIME 2025 | 38.1 | 550 | 8th | |
| LiveCodeBench | 40.2 | 537 | 11th | |
| IFEval | 63.4 | 543 | 10th | |
| TruthfulQA | 58.0 | 548 | 9th | |
| HellaSwag | 68.5 | 553 | 8th | |
| MMMU | 49.4 | 556 | 7th | |
| Arena Elo | 1204.8 | 548 | 9th |
What MiniMax-Text 1.5B is good for
MiniMax-Text 1.5B 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 $0.58 per million input tokens it can handle a large share of production traffic.
Strengths
- Input price of $0.58 per million tokens is at or below the index median.
- Open weights make self-hosting, fine-tuning and data-residency review possible.
Trade-offs
- 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 |
|---|---|---|---|---|
| DBRX 7B | Databricks | 8192 | $0.65 | 51.9 |
| OLMo 2 7B | Allen Institute for AI | 16384 | $0.56 | 51.7 |
| QwQ 1.5B | Alibaba Cloud | 32768 | $0.61 | 51.6 |
| MiniMax-Text 1.5B | MiniMax | 32768 | $0.58 | 51.5 |
| Phi-3.5 8B | Microsoft | 16384 | $0.59 | 51.2 |
| DeepSeek-Coder 1.5B | DeepSeek | 16384 | $0.58 | 51.0 |
FAQ
How much does MiniMax-Text 1.5B cost?
MiniMax-Text 1.5B is listed at $0.58 per million input tokens and $2.90 per million output tokens. Cached input is $0.060 per million tokens. A blended 3:1 input-to-output mix is about $1.16 per million tokens.
What is the context window of MiniMax-Text 1.5B?
MiniMax-Text 1.5B has a context window of 32,768 tokens and can emit up to 16,384 output tokens per request in this index.
Is MiniMax-Text 1.5B open weights?
Yes. MiniMax-Text 1.5B is listed as an open-weight model under a open weights licence.
How does MiniMax-Text 1.5B score on benchmarks?
MiniMax-Text 1.5B averages 51.5 across the scored benchmarks in this index, ranking #545 of 600 models. Its strongest relative result is Arena Elo at 1204.8.
What is MiniMax-Text 1.5B best for?
MiniMax-Text 1.5B 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 $0.58 per million input tokens it can handle a large share of production traffic.