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Mistral Large 3 vs Qwen3.8 Max

Compare Mistral Large 3 from Mistral and Qwen3.8 Max from Qwen on key metrics including benchmarks, price, context length, and other model features. Access both models and hundreds of others through the AIHubMix API.

MistralMistral Large 3QwenQwen3.8 Max
Mistral logo
Mistral Large 3
Mistral · text, image → text

Mistral Large 3 is a MoE model with 67.5B total parameters and 41B active parameters, supporting a 256K-token context window. Trained from scratch on 3,000 NVIDIA H200 GPUs, it is one of the strongest permissively licensed open-weight models available. Designed for advanced reasoning and long-context understanding, Mistral Large 3 delivers performance on par with the best instruction-tuned open-weight models for general-purpose tasks, while also offering image understanding capabilities. Its multilingual strengths are particularly notable for non-English/Chinese languages, making it well-suited for global applications. Typical use cases include enterprise assistants, multilingual customer support, content generation and editing, data analysis over long documents, code assistance, and research workflows that require handling large corpora or complex instructions. With its MoE architecture, Mistral Large 3 balances strong performance with efficient inference, providing a versatile backbone for building reliable, production-grade AI systems.

Input$0.5 /M
Output$1.5 /M
Qwen logo
Qwen3.8 Max
Qwen · text, image, video → text

Qwen3.8-Max is Alibaba Cloud Tongyi Qianwen's next-generation flagship large language model, featuring a mixture-of-experts (MoE) architecture with 2.4 trillion parameters. It achieves another breakthrough in encoding depth, enabling it to handle more complex engineering-grade projects and long-term autonomous development; collaborative agent capabilities are significantly enhanced, performing more confidently in multi-tool orchestration and end-to-end delivery; visual understanding is comprehensively improved, with more sensitive and accurate chart reasoning, document parsing, and multimodal perception. Continuing the 1-million-context window, reasoning modes, and a complete tool ecosystem, it continues to evolve at a higher level of intelligence.

Input$1.69 /M
Output$5.07 /M
Cache read$0.169 /M

Pricing & Specifications

Prices are per million tokens. Time to First Token and throughput are rolling averages measured on AIHubMix.

Mistral Large 3
Qwen3.8 Max
Input /M
$0.5
$1.69
Output /M
$1.5
$5.07
Cache read /M
-
$0.169
Context length
256,000
1,000,000
Max output
131,072
131,072
Time to First Token
2.6 s
12.5 s
Throughput
60.2 tok/s
28.4 tok/s
Modalities
textimage
textimagevideo
Supported Parameters
function callingstructured outputs
toolsfunction callingstructured outputsweblong contextthinking
API Formats
Released
November 1, 2024
August 3, 2026

Promotional prices show the discounted rate; see each model page for promotion windows.

Activity Past 30 Days

Daily traffic served through AIHubMix — how demand for each model is trending.

mistral-large-3qwen3.8-max

Tokens / day

-

Requests / day

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Performance Past 3 Days

Measured on real AIHubMix traffic, hourly buckets. Gaps mean no traffic in that hour.

mistral-large-3qwen3.8-max

Throughput (tok/s)

-

TTFT (s)

-

Uptime (%)

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LMArena Benchmarks

LMArena ratings by capability (Bradley-Terry, commonly called Elo). Higher is better.

Text
mistral-large-3qwen3.8-max
1360140014401480
Overall
14161482
Coding
14681468
Math
14021402
Hard prompts
14321432
Instruction following
14041404
Multi-turn
14211421
Creative writing
13761376
Longer query
14171417
Chinese
14271427
English
14291429
WebDev Arena
mistral-large-3qwen3.8-max
1200134014801620
Overall
12241672
HTML
12301230

Source: LMArena (arena.ai) leaderboard, imported by AIHubMix. Models without published ratings are omitted per chart.

Cost calculator

Estimate your monthly bill for the same workload on each model.

Mistral Large 3
$52.50 /mo
Qwen3.8 Max
$177 /mo

Monthly = daily × 30. Discounted rates applied where a promotion is active.

FAQ

Which is cheaper: Mistral Large 3, Qwen3.8 Max?

Mistral Large 3: $1.5/M output tokens; Qwen3.8 Max: $5.07/M. Use the cost calculator above to estimate your own workload.

Which responds faster?

Mistral Large 3: 2.6s time to first token measured on AIHubMix; see the live performance charts above for how each model behaves across the day.

How large is each context window?

Mistral Large 3 accepts 256,000 and Qwen3.8 Max accepts 1,000,000 input tokens. Maximum output per request is 131,072 tokens on Mistral Large 3 and 131,072 tokens on Qwen3.8 Max.

Which one generates tokens faster?

Mistral Large 3 at 60.2 tok/s and Qwen3.8 Max at 28.4 tok/s, measured as output throughput on AIHubMix — a separate metric from time to first token.

What inputs and capabilities does each model support?

Mistral Large 3 accepts text and image input and supports function calling and structured outputs; Qwen3.8 Max accepts text, image and video input and supports tool calling, function calling, structured outputs, web search, long context and thinking.

Can I call Mistral Large 3 and Qwen3.8 Max with the same API key?

Yes. AIHubMix serves every model on this page behind one OpenAI-compatible endpoint, so switching between them is a one-line change to the model field — no second account, key or SDK.

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