Which is cheaper, Gemini 1.0 Pro or MiniMax M1 80K?
As of August 20, 2026, Gemini 1.0 Pro is 27% cheaper on blended LLM API pricing. Gemini 1.0 Pro costs $0.50 per million input tokens and $1.50 per million output tokens ($2.00 blended 1M-in + 1M-out). MiniMax M1 80K costs $0.55 / $2.20 per million tokens ($2.75 blended). Sources: https://ai.google.dev/gemini-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 Gemini 1.0 Pro vs MiniMax M1 80K cost per million tokens?
Gemini 1.0 Pro Gemini API pricing is $0.50 input and $1.50 output per million tokens via Google. MiniMax M1 80K MiniMax API pricing is $0.55 input and $2.20 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, Gemini 1.0 Pro or MiniMax M1 80K?
MiniMax M1 80K has a published SWE-bench Verified score of 56%. Gemini 1.0 Pro does not have that eval on this page yet.
What is the context window for Gemini 1.0 Pro vs MiniMax M1 80K?
Gemini 1.0 Pro supports a 33K token context window, while MiniMax M1 80K supports 1M tokens. MiniMax M1 80K 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, Gemini 1.0 Pro or MiniMax M1 80K?
MiniMax M1 80K leads on 1 of 1 shared benchmarks versus Gemini 1.0 Pro's 0 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 Gemini 1.0 Pro or MiniMax M1 80K better for production use?
Both Gemini 1.0 Pro and MiniMax M1 80K are production API models. For cost-sensitive production traffic, Gemini 1.0 Pro 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 Gemini 1.0 Pro and MiniMax M1 80K in my app?
Yes. Call Gemini 1.0 Pro through Google and MiniMax M1 80K 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 Gemini 1.0 Pro vs MiniMax M1 80K pricing data?
List rates are the latest published Gemini API pricing and MiniMax API pricing, quoted per million tokens. Official rate sheets: https://ai.google.dev/gemini-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 Gemini 1.0 Pro and MiniMax M1 80K?
Gemini 1.0 Pro supports up to 8K output tokens per request, while MiniMax M1 80K supports up to 40K 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, Gemini 1.0 Pro or MiniMax M1 80K?
Gemini 1.0 Pro has a measured throughput of approximately 120 tokens/second. Throughput data for MiniMax M1 80K 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 Gemini 1.0 Pro vs MiniMax M1 80K comparison?
Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open Gemini 1.0 Pro or MiniMax M1 80K from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.
