gpt-oss-20b (free) is free for input tokens while MiniMax M2.1 costs $0.29 per 1M tokens.
API cost decision in 10 seconds
gpt-oss-20b (free) vs MiniMax M2.1
Pick gpt-oss-20b (free) for lower cost; pick MiniMax M2.1 only if the larger context window matters more.
Page updated:
Data confirmed:
Prices normalized to USD per 1M tokens
Sample workload: 1M input + 500K output
Budget verdict
Pick gpt-oss-20b (free) for lower cost; pick MiniMax M2.1 only if the larger context window matters more.
On the standard 1M input plus 500K output workload, gpt-oss-20b (free) is estimated at $0 vs $0.76 for MiniMax M2.1, saving $0.76 (100% lower).
Cost-first pickgpt-oss-20b (free)
Context-first pickMiniMax M2.1
Sample savings$0.76100%
10x traffic gap$7.65
MiniMax M2.1 has more context, but gpt-oss-20b (free) saves $0.76 on the standard workload. At 10x that traffic, the same price gap is about $7.65. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
gpt-oss-20b (free) stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | gpt-oss-20b (free) | MiniMax M2.1 |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | gpt-oss-20b (free) | $0 | $1.92 |
| Balanced workload | 1M input + 1M output | gpt-oss-20b (free) | $0 | $1.24 |
| Output-heavy chatbot | 1M input + 5M output | gpt-oss-20b (free) | $0 | $5.04 |
gpt-oss-20b (free) is free for output tokens while MiniMax M2.1 costs $0.95 per 1M tokens.
MiniMax M2.1 has 73.73K more context (1.56x larger).
gpt-oss-20b (free) is free for the standard workload while the other model is estimated at $0.76.
Estimate your workload cost
Your Workload Cost
This estimate uses normalized public API pricing per 1M tokens. It is a planning aid, not a billing quote. Verify provider pricing, limits, and terms before production use.
Quick Decision
gpt-oss-20b (free) has the lower input price; gpt-oss-20b (free) has the lower output price; MiniMax M2.1 offers the larger context window. For the 1M input plus 500K output sample, gpt-oss-20b (free) is cheaper for the standard workload.
For a 1M input token plus 500K output token workload, the estimated API cost is $0 for gpt-oss-20b (free) and $0.76 for MiniMax M2.1.
Choose gpt-oss-20b (free) when you care most about lower input-token price, and lower output-token price.
Choose MiniMax M2.1 when you care most about larger context window.
- On the standard 1M input plus 500K output workload, gpt-oss-20b (free) is estimated at $0 vs $0.76 for MiniMax M2.1, saving $0.76 (100% lower).
- gpt-oss-20b (free) is free for the standard workload while the other model is estimated at $0.76.
- gpt-oss-20b (free) is free for input tokens while MiniMax M2.1 costs $0.29 per 1M tokens.
- gpt-oss-20b (free) is free for output tokens while MiniMax M2.1 costs $0.95 per 1M tokens.
- MiniMax M2.1 has 73.73K more context (1.56x larger).
| Feature | gpt-oss-20b (free) (OpenAI) | MiniMax M2.1 (MiniMax) |
|---|---|---|
| Input Price prompt tokens per 1M | $0 | $0.29 |
| Completion Price per 1M tokens | $0 | $0.95 |
| Sample Workload Cost 1M input + 500K output | $0 | $0.76 |
| Context Window | 131.07K | 204.8K |
| Release Date | ||
| Popularity | #72 | #118 |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | gpt-oss-20b (free) | On the standard 1M input plus 500K output workload, gpt-oss-20b (free) is estimated at $0 vs $0.76 for MiniMax M2.1, saving $0.76 (100% lower). |
| High-volume input processing | gpt-oss-20b (free) | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | gpt-oss-20b (free) | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | MiniMax M2.1 | A larger context window leaves more room for retrieved passages, conversation history, or source files. |
Related Alternatives
- MiniMax M2.5 (free) can replace MiniMax M2.1 when lower sample workload cost matters most: $0.
- MiniMax M2.5 can replace MiniMax M2.1 when lower sample workload cost matters most: $0.72.
- MiniMax-01 can replace MiniMax M2.1 when lower sample workload cost matters most: $0.75.
- MiniMax M2 can replace MiniMax M2.1 when lower sample workload cost matters most: $0.76.
- Llama 4 Scout offers 10M context with $0.23 sample workload cost.
- Owl Alpha offers 1.05M context with $0 sample workload cost.
- DeepSeek V4 Flash offers 1.05M context with $0.2 sample workload cost.
- DeepSeek V4 Pro offers 1.05M context with $0.87 sample workload cost.
- DeepSeek V4 Flash · DeepSeek · #1
- Hy3 preview · Tencent · #2
- Claude Opus 4.7 · Anthropic · #3
- Claude Sonnet 4.6 · Anthropic · #4
Cheaper alternatives
Review low-cost models sorted by a standard 1M input plus 500K output workload.
Open cheapest modelsLarger context alternatives
Find models with larger context windows for RAG, long documents, and codebase review.
Open largest context modelsProvider catalogs
Compare models within provider hubs before choosing a final API vendor.
Open provider hubsOpenAI catalog
Review all tracked OpenAI models before deciding whether this matchup is the right shortlist.
Open OpenAI modelsMiniMax catalog
Check other MiniMax models with comparable pricing, context, or release timing.
Open MiniMax modelsgpt-oss-20b is an open-weight 21B parameter model released by OpenAI under the Apache 2.0 license. It uses a Mixture-of-Experts (MoE) architecture with 3.6B active parameters per forward pass, optimized for...
MiniMax-M2.1 is a lightweight, state-of-the-art large language model optimized for coding, agentic workflows, and modern application development. With only 10 billion activated parameters, it delivers a major jump in real-world...