Artificial Analysis has given Mistral Large 4 an Intelligence Index score of 38, putting it level with GPT-6 Luna (max) and DeepSeek V4.1 Flash (max). France is back in the seat of "the strongest model from outside the US and China." The 38-point mark puts Korean and UAE-developed models in their place. Le Chonk (a deliberately self-deprecating nickname, French for "the chonk") was trained from scratch on 3,800 NVIDIA Grace Blackwell GPUs in Mistral's own European data centers.
What the Intelligence Index 38 actually means
Under Artificial Analysis's methodology, the Intelligence Index folds reasoning, agentic, coding, and knowledge tasks into a single comparable score. Le Chonk's 38 sits in the most crowded band of open-weight models: DeepSeek V4.1 Flash (max) is 39, GLM-5.3-Flash sits around 36, and Qwen3.8 Max and Kimi K3 land in the 35-37 range. Compared with Mistral Large 3 on the same methodology, the new model lifts the score by 12 points. Mistral raised the multimodal input ceiling to 100 images per request (up from 8 on older Mistral models) — that change is the key driver on this curve. Document charts, satellite imagery, and engineering drawings — inputs where images outnumber words — no longer need to be sliced and reassembled.
Beyond the Intelligence Index, Artificial Analysis's Cyber Index gave 50, tied with GLM-5.3-Flash and behind MiMo-V2.6-Pro (56). On the CyberGym-E2E-AA sub-test, Le Chonk scored 82%, ahead of MiMo-V2.6-Pro (79%) and GPT-6 Luna (max, 78%). This is the specific field where open-weight models stop being blocked by refusals.
The cost curve is still hard beyond the "two-week half-price" window
Mistral puts single-task cost on the comparison chart's x-axis. List price is $1.13 per task; during the first two weeks, the launch discount brings it down to $0.56 per task. Against GLM-5.3-Flash ($0.25) and DeepSeek V4.1 Flash (max, $0.27), that's still roughly 4x more costly. Their explanation: the first two weeks are for getting hands-on time, and after the weights open, self-hosted deployment costs drop back to the hardware layer rather than the API sticker layer. For European customers, this is the number that actually matters for compliance: running on their own infrastructure, tokens never leave the data center, and the bill is on compute rather than per token.
Standard pricing is $1.36 / $4.18 per million input/output tokens ($0.14 per million cached input), 512k context, text and image in, text out. Mistral operates independently in Europe, which fits the "sovereign AI" narrative. The cost is that, at the same Intelligence Index score, the per-token price is still a step above Chinese open-weight models.
"Not China and not the US" is itself a kind of insurance
Le Chonk is not a technical breakthrough — 38 on the Intelligence Index is not rare in October 2026 — the actual news angle is supply-source diversification. France plus European self-built data centers plus full open weights landing at month-end plus a sovereignty narrative is a packaged answer to enterprises caught between "can't use Chinese models" and "can't use only American models." Microsoft-Mistral's Vera Rubin GPU sovereign cloud agreement from a few weeks back is the other end of the same curve. The Artificial Analysis piece is putting a price tag on that curve.
After end-of-month open-weights, if the community runs further fine-tuning on Mistral's training recipe and pushes 38 into the 40-42 range, Le Chonk becomes the new default baseline for European open-weight models. Until then, the 38 itself, alongside Korean Solar Mini 4 (24) and UAE-developed models in the same band, is enough to put "France's LLM is back" on this year's list of side headlines.