iTechGuides is reader-supported. When you buy through links on our site, we may earn an affiliate commission. As an Amazon Associate I earn from qualifying purchases. Learn more
Mistral Large 4, nicknamed “Le Chonk,” launched on October 6, 2026, as a public preview API—not as downloadable model weights. Mistral describes it as a trillion-parameter multimodal model and says it leads open-weight models outside China on some measures. That ranking is Mistral’s claim, not an independently established comparison across named Chinese competitors. At launch, Mistral said the weights would arrive later in October; Reuters reported October 27 as the planned public release date.
What is Mistral Large 4, or “Le Chonk”?
Mistral Large 4 is the official model name; “Le Chonk” is its nickname. Mistral announced it on October 6, 2026, and described it as natively multimodal, with 1 trillion total parameters and 49 billion active parameters. Those figures are the company’s specifications.
Mistral also said it trained the model on 3,800 NVIDIA Grace Blackwell GPUs in its European datacenters. That describes Mistral’s training infrastructure, not the hardware a customer needs to run the model. Mistral had not yet published final inference requirements at launch.
Quick wins for a faster PC:
Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →Clear out junk files and repair common Windows errorsFree Scan →Is Mistral Large 4 available yet?
Preview API
Yes. At launch, Mistral offered a public preview API through Mistral Studio. Mistral’s announcement said: “Today, we’re launching a public preview of Mistral Large 4. Unofficially ML4, very officially: le Chonk.” Preview access means users can try the hosted model; it does not mean the model weights are downloadable.
#1 Best Overall
- High-Performance AI Processor：The MS-02 Ultra features an Intel Core Ultra 9 285HX (24C/24T, up to 5.5 GHz, 13 TOPS NPU), delivering fast and efficient performance for AI inference, algorithm development, and media workloads. A PCIe x16 expansion slot supports desktop-class GPU upgrades for advanced model training and accelerated computing tasks. It's ideal for creators, engineers, and teams handling intensive parallel workloads.
- 4 × M.2 PCIe 4.0 + 4 × DDR5 SODIMM slots:Four DDR5 SODIMM slots support up to 256 GB of memory, while ECC helps maintain data integrity in mission-critical environments. Four PCIe 4.0 M.2 slots support up to 24 TB of storage, supporting RAID 0/1/5/10, combining high-speed performance with data protection. It allows for the creation of independent scratch disks, media libraries, and project drives, providing high-throughput for production workflows.
- PCIe & USB 4.0 v2: Up to three PCIe slots can be equipped, including a dual-slot x16 GPU. The main slot supports PCIe 5.0, meeting the needs of high-bandwidth creative and computing workloads. USB 4.0 v2 (80Gbps) supports high-bandwidth external storage and displays.
- Ultra-fast Networking: Wi-Fi 7 further enhances wireless performance with next-generation speeds and low-latency stability. Intelligent bandwidth switching optimizes throughput in different network environments, ensuring optimal performance for enterprise or local networks. Dual 25GbE ports (providing up to approximately 3.125 GB/s bandwidth, about 25 times faster than traditional 1GbE), enabling seamless large-scale file transfers and parallel computing. 10GbE and 2.5GbE ports, with support for Intel vPro technology, ensure enterprise-grade remote management and deployment flexibility.
- Server-grade thermal architecture: Utilizing a dedicated CPU/GPU airflow design, equipped with a 6-pipe dual-fan cooler, it maintains stable performance even under sustained loads, delivering up to 140W Turbo power while maintaining a 100W TDP, and operating with noise levels as low as 36 dB. An integrated 350W power supply ensures stable and reliable output for demanding computing tasks and fully loaded extended configurations.
Downloadable weights
No—not at the October 6 launch. Mistral said weights would be released by the end of October, with more architecture information, benchmarks, and post-training methodology. Reuters reported October 27 as the planned public release date. Because these are future release details in launch-day reporting, check Mistral’s current announcement for whether the date, availability, or terms have changed.
The launch sources did not establish the final model license or the hardware needed for self-hosting. “Open-weight” is the term used in the coverage; it should not be read as confirmation that the model meets every definition of open-source software.
What performance claims has Mistral made?
Mistral highlighted coding, agentic workflows, multimodal understanding, cybersecurity, finance, law, and manufacturing. Its launch announcement included the following company-reported results. They refer to different tasks and evaluation methods, so they should not be combined into a single score or treated as independent verification.
| Task or evaluation | Mistral’s reported result |
|---|---|
| Reproducing and patching a real vulnerability in open-source software | 82%; Mistral said this was the highest score on that test |
| Cybench security exercises | 93% of challenges; Mistral described Cybench as 40 exercises |
| DeepSWE v1.1 | 61.7% |
| SWE-Atlas-QnA | 59.4% |
| Terminal-Bench 4 | 28.3% |
| Coding Agent Index | 49.8%; Mistral said it was ahead of DeepSeek V4 Pro 0813 |
| Blind coding-quality evaluation by professional annotators | 3.74 out of 5; Mistral said the preview ranked second among five models |
| AutomationBench business workflows | 59.9% across a set Mistral described as 657 workflows |
| AA-Briefcase | 1,393 Elo |
| Dense 200 visual grounding | 42%, compared with 41% for GPT-6-Astra |
These figures are from Mistral’s October 6, 2026 announcement. The announcement is a company source; the launch reports from WIRED and Reuters provide context and attributed statements but do not independently validate each result. Mistral also said a reinforcement-learning training run using 3,000 GPUs produces roughly 33 billion tokens per day, including around 16 billion trainable completion tokens after filtering and masking. This is a description of Mistral’s training process, not a measure of user-facing model speed.
Rank #3
- Professional AI & Creator Workstation: AMD Radeon AI PRO R9700 GPU with 32GB GDDR6 is engineered for AI development, professional content creation, and compute-intensive workloads.
- Massive 32GB Memory Capacity: 32GB of GDDR6 memory on a 256-bit bus provides ample bandwidth for large AI models, 8K video editing, and complex 3D rendering.
- Advanced RDNA 4 with AI Accelerators: 64 Compute Units with 3rd Gen Ray Tracing and dedicated 2nd Gen AI Accelerators for groundbreaking AI performance and visual computing.
- Professional Blower Cooling: Efficient single blower design exhausts heat directly out of the chassis, ideal for multi-GPU workstation and server configurations.
- Enterprise-Grade Thermal Solution: Vapor chamber heatsink with industrial Honeywell PTM7950 thermal interface material ensures reliable cooling under sustained professional loads.
Is Le Chonk really the best open-weight model outside China?
That is Mistral’s positioning, not a settled independent ranking. The launch reporting does not provide a complete comparison against named Chinese models using a shared set of benchmarks. Reuters reported that CEO Artur Mensch said the model was above Chinese models “on certain aspects, including cyber,” but did not specify which models or benchmarks supported that comparison.
Mistral cofounder and chief scientist Guillaume Lample told WIRED, “There are a lot of areas where the other labs will not focus that much,” and, “Mistral is still in the race of getting the best model.” These comments convey the company’s strategy and ambition; they are not independent evaluation results.
Rank #4
- FAST RUNS IN THE FAMILY — The 16-inch MacBook Pro with the M5 Pro or M5 Max chip brings next-generation speed and powerful on-device AI to personal, professional, and creative tasks. With all-day battery life, double the starting storage,* and a breathtaking Liquid Retina XDR display, it’s pro in every way.*
- BUCKLE UP — Along with a next-generation CPU, faster unified memory, and up to 2x faster SSD storage,* M5 Pro and M5 Max feature a more powerful GPU with a Neural Accelerator built into each core, delivering faster AI performance and on-device training capabilities. So you can blaze through demanding workloads at mind-bending speeds.
- BUILT FOR AI — Apple silicon, and every major component that powers it, is designed to run demanding on-device AI workloads like LLM inference and training. And Apple Intelligence helps you write, express yourself, and get things done effortlessly with groundbreaking privacy protections at every step.*
- ALL-DAY BATTERY LIFE — MacBook Pro delivers the same exceptional performance whether it’s running on battery or plugged in.*
- MACOS RUNS APPS FAST — All your go-to apps run lightning fast in macOS, including built-in apps like FaceTime and Messages. Plus, built-in virus protection and free software updates help keep your Mac running smoothly and securely.
For a meaningful comparison, check the exact benchmark and task, who ran the evaluation, whether models were tested under comparable conditions, and whether the result matches your workload. Also distinguish total parameters from active parameters, hosted API access from self-hosting, and the model’s capabilities from its eventual license and deployment requirements.
Free tools Windows power users keep installed
One-click scans. No signup required.
How much does the Mistral Large 4 API cost?
Mistral listed preview API prices of $1.36 per million input tokens and $4.18 per million output tokens in its October 6, 2026 announcement. These are launch-period prices for the preview API and may change. Check Mistral Studio’s current pricing before estimating a project’s costs.
Quick Recap
Best Value
- 【High-Performance APU】The MS-S1 MAX features an AMD Ryzen AI Max+ 395 APU, integrating a Zen 5 architecture CPU (up to 5.1GHz, 16C/32T, 64M L3 Cache), an RDNA 3.5 GPU, and an NPU (50 TOPS). The total system output is 126 TOPS. It provides powerful parallel computing capabilities for demanding AI workflows. It is ideal for running local LLMs, multimodal models, and computationally intensive tasks
- 【128GB UMA Memory】Equipped with up to 128GB of LPDDR5x-8000MT/s unified memory, it enables the CPU and GPU to access a shared, high-bandwidth memory pool with extremely low latency. Ideal for large-scale AI inference, 3D workloads, and complex timelines in video editing. It eliminates traditional VRAM bottlenecks, ensuring smoother data transfer during high-intensity computations. The UMA design maximizes performance stability under high loads
- 【Flexible Expansion】The MS-S1 MAX features USB4 V2 (up to 80Gbps), dual 10GbE LAN, HDMI 2.1 (up to 8K60), a full-length PCIe x16 expansion slot, and dual M.2 slots supporting up to 16TB RAID 0/1. Wi-Fi 7 provides stronger signal coverage and a more stable wireless experience. The slide-out design facilitates upgrades and maintenance. It easily adapts to personal, studio, or rack-mount enterprise environments
- 【High-Efficiency Cooling System】Utilizing an aerospace-grade aluminum alloy chassis, copper base plate, six heat pipes, dual turbine fans, and advanced PCM thermal conductive material, it maintains stable cooling performance even under continuous load. This system supports 130W continuous power and 160W peak power operation, with a built-in 320W power supply. It boasts multiple global certifications including CCC, FCC, UL, CE, and UKCA, ensuring stable and reliable operation in various environments
- 【Cluster Design】Two MS-S1 MAX units can be configured as a dual-unit cluster to run a large 235B Q4 model locally, achieving an output speed of 10.87 tok/s. Supporting 2U rack deployment, multiple MS-S1 MAX units can be cascaded into a distributed cluster to create a high-efficiency AI computing center. A cluster of four MS-S1 MAX units successfully ran a DeepSeek-R1 671B Q4 large model. A reserved cluster power-on interface allows for unified start-up and shutdown
Where to verify release details
- Mistral’s “Introducing Mistral Large 4” announcement is the primary source for the company’s specifications, reported evaluations, preview access, and launch pricing.
- WIRED’s October 6, 2026 launch report includes context and comments from Mistral cofounder and chief scientist Guillaume Lample.
- Reuters’ October 6, 2026 report, republished by Euronext reports the planned release date and qualifies the CEO’s comparison with Chinese models.
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
