MiniMax M3.1 Flash vs Qwen3 Next 80B A3B Instruct
As of November 12, 2026, Qwen3 Next 80B A3B Instruct and MiniMax M3.1 Flash cost the same per input token ($0.15 per 1M), but Qwen3 Next 80B A3B Instruct costs 100% more per output token ($1.20 vs $0.60) and has a 256K-token context window versus 1M.
MiniMax M3.1 Flash vs Qwen3 Next 80B A3B Instruct side by side
| MiniMax M3.1 Flash | Qwen3 Next 80B A3B Instruct | |
|---|---|---|
| Input, per 1M tokens | $0.15 | $0.15 |
| Output, per 1M tokens | $0.60 | $1.20 |
| Cache read, per 1M tokens | $0.015 | – |
| Cache write, per 1M tokens | – | – |
| Context window | 1,000,000 tokens | 262,144 tokens |
| Max output | 524,288 tokens | 65,536 tokens |
| Image input | Yes | – |
| Tool calling | Yes | Yes |
| Structured output (JSON) | Yes | Yes |
| Prompt caching | Yes | – |
| Reasoning | Yes | Yes |
| Providers on LiteLLM | 9 | 11 |
| Price shown is from | MiniMax | Alibaba Cloud Model Studio |
| Added to LiteLLM | October 19, 2026 | September 2025 |
Cheapest provider for each
- MiniMax M3.1 Flash: Refuseless at $0.05 input and $0.25 output per 1M tokens (
refuseless/minimax-m3.1-flash) - Qwen3 Next 80B A3B Instruct: DeepInfra at $0.09 input and $1.10 output per 1M tokens (
deepinfra/Qwen/Qwen3-Next-80B-A3B-Instruct)
When to pick which
Pick MiniMax M3.1 Flash for
- Costs 50% less per output token: $0.60 vs $1.20 per 1M.
- Larger context window: 1,000,000 vs 262,144 tokens.
From differences in the data above only; where the data is equal, no reason is given.
Call MiniMax M3.1 Flash or Qwen3 Next 80B A3B Instruct with LiteLLM
Both use the OpenAI format through LiteLLM, so switching is a model name change. Set each provider's API key in the environment first.
from litellm import completion
messages = [{"role": "user", "content": "Hello!"}]
# MiniMax M3.1 Flash
response = completion(model="minimax/MiniMax-M3.1-Flash", messages=messages)
# Qwen3 Next 80B A3B Instruct
response = completion(model="dashscope/qwen3-next-80b-a3b-instruct", messages=messages)
# MiniMax M3.1 Flash, falling back to Qwen3 Next 80B A3B Instruct if the call fails
response = completion(model="minimax/MiniMax-M3.1-Flash", messages=messages, fallbacks=["dashscope/qwen3-next-80b-a3b-instruct"])FAQ
Which is cheaper, MiniMax M3.1 Flash or Qwen3 Next 80B A3B Instruct?
MiniMax M3.1 Flash is cheaper at 3 input tokens per output token: $0.2625 per 1M tokens blended ($0.15 input, $0.60 output), versus $0.4125 ($0.15 and $1.20) for Qwen3 Next 80B A3B Instruct, as of November 12, 2026.
Which has the larger context window, MiniMax M3.1 Flash or Qwen3 Next 80B A3B Instruct?
MiniMax M3.1 Flash has the larger context window: 1,000,000 tokens, versus 262,144 for Qwen3 Next 80B A3B Instruct.
Can I switch from MiniMax M3.1 Flash to Qwen3 Next 80B A3B Instruct without changing my code?
Yes. Through LiteLLM both use the OpenAI format, so switching means changing the model name from "minimax/MiniMax-M3.1-Flash" to "dashscope/qwen3-next-80b-a3b-instruct", or pointing a LiteLLM gateway model alias at the other model. You can also use one as a fallback for the other.