Mistral Large 4’s $1.36/$4.18 Card, Audited

"Input (/M tokens) $1.36" and "Output (/M tokens) $4.18" is the rate pair Mistral printed on the Mistral Large 4 product card in its October 6 launch post.

Mistral printed those rates on the Large 4 product card

The numbers sit at the bottom of the same page that introduces the public preview, next to the nickname Le Chonk and the short capability blurb. They are Mistral’s own list prices for API usage, not a third-party estimate and not a leaked enterprise quote.

Mistral frames the release as a preview API on Mistral Studio today, with weights promised by the end of October. The dollar figures appear in that same commercial block. They are not buried in a separate pricing PDF.

That matters because VentureBeat’s October 6 report said the company did not provide API pricing in the materials it reviewed. The launch page itself lists $1.36 and $4.18 on the product card.

TechCrunch’s same-day piece focused on access shape and the open-weight delay rather than dollars. Pierre Stock told TechCrunch the model is on a public guardrail endpoint for now, with weights due in about three weeks after safety work with partners and governments. Pricing was not the headline there. The $1.36 / $4.18 pair still sits on mistral.ai for anyone who opens the announcement.

The pair measures preview API tokens on Mistral-operated GPUs

Literally, $1.36 is what Mistral charges per million input tokens on the preview, and $4.18 is what it charges per million output tokens. That is meter language for hosted inference. It is not a license fee, not a seat price, and not a cost-per-benchmark-run.

The model behind the meter is the one Mistral describes as a 1-trillion-parameter natively multimodal mixture-of-experts system with 49 billion parameters active at inference. Multimodal in, text out, per Guillaume Lample in the VentureBeat interview. The launch card does not disclose whether image prompts change token accounting. It prints only the two headline rates for input and output.

Serving is on the same European Grace Blackwell fleet Mistral cites for training. The company says Large 4 was trained from scratch on 3,800 NVIDIA Grace Blackwell GPUs in its own European datacenters (TechCrunch and VentureBeat round that to about 4,000). The preview runs on that stack. So the $1.36 / $4.18 quote is also a statement about where the bits live: Mistral-operated infrastructure under the preview’s guardrails, not your rack.

Nothing in the published card breaks the rate into reasoning tokens, tool tokens, or cached-prefix discounts. If those exist in Studio’s fine print, Mistral did not put them next to the headline numbers on the launch page. Treat $1.36 and $4.18 as the public sticker for standard input and output until a more granular schedule appears.

Open weights, red-team access, and unfinished RL sit outside the card

Weights are not included in $1.36 / $4.18. The nickname Le Chonk points at the model’s size, not at a downloadable package you get for those rates. Mistral says weights drop by the end of the month. VentureBeat dates that plan to October 27, after roughly three weeks of testing with developers, cybersecurity leaders, and government authorities, under a custom Mistral license the company has not fully spelled out in the cited coverage.

Until then, Stock’s line to TechCrunch is the access rule: trusted partners and governments get a path that can defend without enabling malicious attacks, while the public endpoint stays guardrailed. That parallel track is not priced on the product card. If you are waiting for downloadable weights, the API sticker is a temporary substitute cost, not the long-term unit economics of self-hosting.

Self-hosting cost is the second exclusion. GPU hours, orchestration, and the engineering around Forge-style customization do not appear in the $1.36 / $4.18 pair. Mistral’s sovereignty pitch (European deployment end-to-end, open weights for cyber and regulated workloads) is exactly the pitch that moves spend off the API meter and onto owned or contracted compute. The launch post does not publish a reference cluster size or a dollars-per-token figure for private deployment.

Third exclusion: the preview is still in flight on reinforcement learning. Mistral says the RL run behind the preview continues, that the model shows headroom, and that more architecture detail, benchmarks, and post-training methodology arrive with the weight release. A rate locked to today’s checkpoint can look cheap or expensive relative to next month’s checkpoint without the dollars changing. Capability is moving. The sticker may not.

Fourth exclusion: vertical claims that drive demand. Mistral reports 82% on one Artificial Analysis Cyber Index task (reproduce a real vulnerability, then patch it), 93% on Cybench’s 40 challenges, a 49.8% Coding Agent Index composite ahead of DeepSeek V4 Pro 0813 and Qwen3.8 Max in its tables, 59.9% on AutomationBench, and 42% vs 41% for GPT-6 Astra on Dense 200 in its own comparison. Those scores explain why someone would open the wallet. They do not convert into a monthly bill by themselves, and VentureBeat notes several competitor cells still lack independent public cross-checks while Large 4 is absent from Artificial Analysis’s public boards and the live DeepSWE leaderboard as of that report.

Long agent traces push spend toward the $4.18 line

Mistral’s launch narrative centers long-horizon setups: DeepSWE, Terminal-Bench, AutomationBench, AA-Briefcase, Finch, and Harvey’s Legal Agent. Those are the workloads the company uses to sell coding, finance, and cyber strength, and they are the ones that generate long tool traces, retries, and finished deliverables rather than a short reply.

Agentic coding, finance workflows, and cyber reproduce-and-patch loops therefore lean on the $4.18 side. Output tokens, tool traces, and retries pile up there. A preview that looks inexpensive when most of the bill is input context can look ordinary once the agent writes patches, fills sheets, or walks multi-app business flows of the kind AutomationBench and Finch describe.

Compare that to the open-weight path after late October. If you already run private inference, the relevant number stops being $1.36 / $4.18 and becomes utilization of whatever fleet you assign to a 1T-total / 49B-active MoE. Mistral has not published that private unit cost. The API card is useful for budgeting the three-week preview window. It is a weak proxy for the sovereign deployment story the company is selling to Airbus-scale and public-sector buyers.

Budget also depends on whether you need the reduced-moderation cyber lane Mistral describes in the launch post for cybersecurity leaders, vetted partners, and state authorities during red-teaming. Stock’s TechCrunch line covers the same window in different words: trusted partners and governments get a path that can defend without enabling malicious attacks. That lane is not for every Studio signup. Paying $4.18 per million output tokens on the public guardrailed endpoint does not purchase the same refusal profile as the partner track, and it does not purchase the eventual on-prem weights. Three different products share one model name in the headlines.

Against other hosted flags people will shop, the launch card still leaves a gap: Mistral has not published a side-by-side rate table on that page against Claude Opus 5, GPT-6 Astra, or DeepSeek V4 Pro.

Those rates describe the guardrailed Studio preview only. They go silent the day you leave that meter for the October 27 weights VentureBeat dates, because the launch card never prices private deployment.