Free to start

MiniMax: MiniMax M3 vs OpenAI: GPT-6.1 Sol

Try both on us. Starter credit covers your first requests, then one key routes MiniMax M3 and GPT-6.1 Sol. Switch by changing the model name.

Compare routesProviders, price, context, and policy posture in one view.

Use auto when uptime mattersKeep a primary model and let fallback handle provider failures.

Same API shapeUse the OpenAI client and set the model you want.

Practical read

Monthly evidence

MiniMax: MiniMax M3 has the lower published input-plus-output rate and more Credits provider routes. GPT-6.1 Sol has the larger context window. There is not enough recent probe data to compare speed.

$1.25545/1MMiniMax: MiniMax M3 cheapest route

$12.66/1MOpenAI: GPT-6.1 Sol cheapest route

not enough dataMiniMax: MiniMax M3 fastest measured p50 TTFT

not enough dataOpenAI: GPT-6.1 Sol fastest measured p50 TTFT

The price comparison adds each route's rate for one million input tokens and one million output tokens; your cost depends on your input/output mix. Prices and live route measurements can change. Use the monthly reports when you need a stable evidence window, then run a small task-specific eval before choosing a production default.

MiniMax: MiniMax M3OpenAI: GPT-6.1 Sol

Model idminimax/minimax-m3openai/gpt-6.1-sol

Publisher MiniMax OpenAI

AI IQ IQ 115#55 IQ 141#1

Context1,048,576 tokens1,050,000 tokens

Credits provider routes151

Cheapest route$1.25545/1M$12.66/1M

Cached input$0.05275/1M to $0.2532/1M$0.1055/1M to $0.211/1M

Privacy posturehas ZDR routehas ZDR route

Fastest measured p50 TTFTnot enough datanot enough data

Highest measured throughputnot enough datanot enough data

Recent route uptime rangenot enough datanot enough data

Modes chat chat

MiniMax: MiniMax M3 routes

Overview15 Credits routes
PricingInput, cached input, and output rates
BenchmarksTrustedRouter and external sources
ProvidersAll serving providers

OpenAI: GPT-6.1 Sol routes

Overview1 Credits routes

Related comparisons

Browse every comparison

MiniMax: MiniMax M3 vs Z.ai: GLM 5.348 combined provider routes
MiniMax: MiniMax M3 vs Z.ai: GLM 5.247 combined provider routes
MiniMax: MiniMax M3 vs Z.ai: GLM 5.3 Flash47 combined provider routes
MiniMax: MiniMax M3 vs MoonshotAI: Kimi K343 combined provider routes
DeepSeek: DeepSeek V4 Flash 0731 vs MiniMax: MiniMax M341 combined provider routes
DeepSeek: DeepSeek V4.1 Flash vs MiniMax: MiniMax M339 combined provider routes
MiniMax: MiniMax M3 vs OpenAI: gpt-oss-120b38 combined provider routes
MiniMax: MiniMax M3 vs Qwen: Qwen3.8 27B34 combined provider routes

Production choice

Pick a default model. Keep fallback enabled.

TrustedRouter is useful when you know the model you want, but still need provider rollover, budget limits, usage records, and a prompt path you can verify.

OpenAI clientPython

client = OpenAI(
    base_url="https://api-azure.trustedrouter.com/v1",
    api_key="sk-tr-v1-..."
)

response = client.chat.completions.create(
    model="minimax/minimax-m3",
    messages=messages,
)

Questions

Which should I use, MiniMax: MiniMax M3 or OpenAI: GPT-6.1 Sol?

MiniMax: MiniMax M3 has the lower published input-plus-output rate and more Credits provider routes. GPT-6.1 Sol has the larger context window. There is not enough recent probe data to compare speed.

Is MiniMax: MiniMax M3 or OpenAI: GPT-6.1 Sol cheaper?

The current cheapest TrustedRouter route is $1.25545/1M for MiniMax: MiniMax M3 and $12.66/1M for OpenAI: GPT-6.1 Sol. The comparison uses current catalog prices and updates as provider pricing changes.

Is MiniMax: MiniMax M3 or OpenAI: GPT-6.1 Sol faster?

Current measured p50 time to first token is not enough data for MiniMax: MiniMax M3 and not enough data for OpenAI: GPT-6.1 Sol. These are routed probe measurements, not vendor-advertised speeds, and update as new samples arrive.

Can I test MiniMax: MiniMax M3 and OpenAI: GPT-6.1 Sol with the same API?

Yes. Use the same OpenAI-compatible TrustedRouter base URL and API key, then change only the model id between minimax/minimax-m3 and openai/gpt-6.1-sol. This makes side-by-side evals possible without maintaining two provider integrations.