Which is cheaper, GPT OSS 120B or MiniMax M2.1?
As of August 20, 2026, GPT OSS 120B is 64% cheaper on blended LLM API pricing. GPT OSS 120B costs $0.09 per million input tokens and $0.45 per million output tokens ($0.54 blended 1M-in + 1M-out). MiniMax M2.1 costs $0.30 / $1.20 per million tokens ($1.50 blended). Sources: https://developers.openai.com/api/docs/pricing and https://anotherwrapper.com/tools/llm-pricing. The cheapest LLM for your app still depends on how many output tokens you generate.
How much does GPT OSS 120B vs MiniMax M2.1 cost per million tokens?
GPT OSS 120B OpenAI API pricing is $0.09 input and $0.45 output per million tokens via OpenAI. MiniMax M2.1 MiniMax API pricing is $0.30 input and $1.20 output per million tokens via MiniMax. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.
Which is better for coding, GPT OSS 120B or MiniMax M2.1?
MiniMax M2.1 leads on SWE-bench Verified: GPT OSS 120B at 33.6% vs MiniMax M2.1 at 67%. SWE-bench measures real GitHub fixes; LiveCodeBench measures contest programming.
What is the context window for GPT OSS 120B vs MiniMax M2.1?
GPT OSS 120B supports a 131K token context window, while MiniMax M2.1 supports 1M tokens. MiniMax M2.1 offers a larger context window. Filling a larger window bills more input tokens, so the cheaper-per-million model can still cost more on long documents.
Which model performs better on benchmarks, GPT OSS 120B or MiniMax M2.1?
MiniMax M2.1 leads on 9 of 15 shared benchmarks versus GPT OSS 120B's 6 wins. Check the comparison table for GPQA Diamond, SWE-bench, MMLU, HLE, and the other evals we track. Token price and benchmark score together are the usual LLM comparison, not either number alone.
Is GPT OSS 120B or MiniMax M2.1 better for production use?
Both GPT OSS 120B and MiniMax M2.1 are production API models. For cost-sensitive production traffic, GPT OSS 120B has better economics on the blended 1M-in + 1M-out scale. For maximum capability, weight the benchmark table for your domain. Many production stacks route cheap models for drafts and a frontier model for the hard turn, which is usually cheaper than sending everything to the expensive API.
Can I switch between GPT OSS 120B and MiniMax M2.1 in my app?
Yes. Call GPT OSS 120B through OpenAI and MiniMax M2.1 through MiniMax with separate API keys, or through a gateway that already wraps both. Keep prompts in tokens, not characters, when you estimate the invoice. AnotherWrapper templates can swap providers without rewriting auth and billing.
How accurate is this GPT OSS 120B vs MiniMax M2.1 pricing data?
List rates are the latest published OpenAI API pricing and MiniMax API pricing, quoted per million tokens. Official rate sheets: https://developers.openai.com/api/docs/pricing and https://anotherwrapper.com/tools/llm-pricing. Prompt caching, batch APIs, and committed-use discounts can change the invoice. Benchmark scores are from official publications and independent evals, updated as new numbers land.
What is the output token limit for GPT OSS 120B and MiniMax M2.1?
GPT OSS 120B supports up to 131K output tokens per request, while MiniMax M2.1 supports up to 1M output tokens. Output tokens are usually the expensive half of API pricing, so a higher max output cap is a capability, not a discount.
Which model has better throughput, GPT OSS 120B or MiniMax M2.1?
MiniMax M2.1 has a measured throughput of approximately 100 tokens/second. Throughput data for GPT OSS 120B is not yet available. Throughput (tokens per second) and time-to-first-token are why two models with the same per-million-token price can still feel different in chat and agents.
How do I switch the models in this GPT OSS 120B vs MiniMax M2.1 comparison?
Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open GPT OSS 120B or MiniMax M2.1 from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.
