Head to head
DeepSeek V4 Pro vs Mistral Large 3
DeepSeek V4 Pro (DeepSeek) and Mistral Large 3 (Mistral) compared on intelligence, speed, context, and price — and which to choose. Both run on just4o.chat from one chat.
| Metric | DeepSeek V4 Pro | Mistral Large 3 |
|---|---|---|
| Intelligence (AA index) | 44 ✓ | 16 |
| Output speed (tokens/sec) | 88.2 ✓ | 49.1 |
| Context window | 1.0M ✓ | 256K |
| Max output | 384K | — |
| Input price / 1M | $0.435 ✓ | $0.5 |
| Output price / 1M | $0.87 ✓ | $1.5 |
| Released | 2026-04-24 | 2025-12 |
Choose DeepSeek V4 Pro if you want…
- Higher intelligence (Artificial Analysis index 44)
- Faster output (~88.2 tokens/sec)
- Lower price ($0.54 / 1M blended)
- Larger context window (1.0M)
Choose Mistral Large 3 if you want…
- A comparable all-rounder — they trade blows on the headline metrics.
DeepSeek V4 Pro
DeepSeek V4 Pro makes a compelling case that frontier-class coding performance and a one-million-token context window do not have to cost frontier-class money. At roughly $0.18 per million tokens blended, it runs 10x cheaper on input and 30x cheaper on output than comparable models, while posting an 80.6% score on SWE-Bench Verified — the highest reported among open-weight models at launch. Users consistently praise its agentic coding ability, noting it competes with or beats larger closed models on multi-step coding tasks, and its hybrid attention architecture handles full-codebase analysis without collapsing under the token budget. The MIT license is a genuine differentiator: weights are freely available for self-hosting, fine-tuning, and commercial integration. The honest caveat: V4 Pro is verbose. It can generate four to five times more output tokens than comparable models on the same prompt, which erodes the per-token savings and makes cost estimation harder than it first appears. Still in preview as of mid-2026, with all benchmark scores currently vendor-reported, it is best suited for teams comfortable with that tradeoff.
Full DeepSeek V4 Pro details →Mistral Large 3
Mistral Large 3 is the French lab's flagship dense model, and on just4o.chat it runs through the Vercel AI Gateway under the mistral/mistral-large-3 route. It pairs strong general reasoning with the multilingual fluency Mistral is known for — European languages in particular — and reliable function calling for tool-driven workflows. A 256k-token context window is roomy enough for long documents, multi-file code, or extended chats without truncation, and at $0.50 per million input and $1.50 per million output tokens it sits at the affordable end of frontier-class models. On just4o.chat it is a base-tier model available on every plan, billed at 2 base requests per send before length multipliers. One practical note worth flagging up front: like the rest of the Mistral lineup here, it has no native web search, and it is text-only — no image input. For teams that want a capable, cost-disciplined generalist with first-rate multilingual handling, it is an easy default.
Full Mistral Large 3 details →FAQ
Which is better, DeepSeek V4 Pro or Mistral Large 3?
DeepSeek V4 Pro leads on 4 of the headline metrics (higher intelligence (artificial analysis index 44); faster output (~88.2 tokens/sec); lower price ($0.54 / 1m blended); larger context window (1.0m)), while Mistral Large 3 wins on other factors. The right pick depends on whether you prioritise capability, speed, or cost.
Is DeepSeek V4 Pro or Mistral Large 3 cheaper?
DeepSeek V4 Pro is cheaper at $0.54 per 1M tokens (blended), versus $0.75.
Can I use both DeepSeek V4 Pro and Mistral Large 3?
Yes. Both are available on just4o.chat from a single chat — you can switch between them per message with no separate subscriptions.