Mistral Releases Medium 3.5: 128B Model with Cloud Coding Agents and 77.6% SWE-Bench Verified
Mistral AI released Medium 3.5, a 128B dense model with a 256k context window that scores 77.6% on SWE-Bench Verified. The model powers new remote coding agents in Mistral Vibe that run asynchronously in the cloud, plus a new Work mode in Le Chat for multi-step agentic tasks.
Mistral Medium 3.5 — Quick Specs
Mistral Releases Medium 3.5: 128B Model with Cloud Coding Agents and 77.6% SWE-Bench Verified
Mistral AI released Mistral Medium 3.5, a 128B dense model with a 256k context window, built for long-running coding and productivity tasks. The model scores 77.6% on SWE-Bench Verified and 91.4 on τ³-Telecom, according to Mistral.
Mistral Medium 3.5 is now available in public preview under a modified MIT open-weights license. The company claims the model can run self-hosted on as few as four GPUs and combines instruction-following, reasoning, and coding in a single set of weights.
Performance and Technical Details
According to Mistral, the model outperforms Devstral 2 and Qwen 3.5 397B A17B on SWE-Bench Verified with its 77.6% score. The model includes a vision encoder trained from scratch to handle variable image sizes and aspect ratios.
Reasoning effort is configurable per request, allowing the same model to handle quick chat replies or complex agentic workflows. Mistral built the model specifically for long-horizon tasks with reliable tool calling and structured output.
Pricing and Availability
Mistral Medium 3.5 is priced at $1.50 per million input tokens and $7.50 per million output tokens via API. Open weights are available on Hugging Face. The model is also available through NVIDIA's build.nvidia.com platform and as NVIDIA NIM containerized inference microservices.
Remote Coding Agents in Vibe
Mistral launched remote coding agents in Vibe CLI that run asynchronously in the cloud. Users can start coding sessions from either the CLI or Le Chat web interface, with sessions running in isolated sandboxes while users step away.
Local CLI sessions can be "teleported" to the cloud, preserving session history, task state, and approvals. The agents integrate with GitHub for pull requests, Linear and Jira for issues, Sentry for incidents, and Slack or Teams for notifications.
According to Mistral, the system is designed for high-volume coding work like module refactors, test generation, dependency upgrades, and bug fixes. Multiple coding sessions can run in parallel.
Work Mode in Le Chat
Mistral introduced Work mode in Le Chat (Preview), powered by Medium 3.5, for multi-step agentic tasks beyond coding. The mode enables cross-tool workflows, research and synthesis, inbox triage, and issue creation in project management tools.
In Work mode, connectors are enabled by default, allowing the agent to access documents, mailboxes, calendars, and other systems. Every tool call and reasoning step is visible to users, with explicit approval required for sensitive actions like sending messages or modifying data.
What This Means
Mistral's combination of a strong open-weights coding model with cloud-based agent infrastructure directly addresses the friction in current AI coding workflows, where developers must babysit agent runs. The 77.6% SWE-Bench Verified score positions Medium 3.5 competitively against larger models, while the claimed four-GPU deployment requirement could enable wider self-hosting.
The $1.50/$7.50 pricing undercuts similar-capability models from competitors, though real-world performance on complex codebases will determine adoption. The integration of coding agents into Le Chat and the new Work mode signals Mistral's push beyond chat interfaces into persistent, multi-step autonomous workflows.
Related Articles
OpenAI releases GPT-5.6 with three model variants, claims 80-point Coding Agent Index score for Sol
OpenAI released GPT-5.6 in three variants: Sol ($5 input/$30 output per 1M tokens), Terra ($2.50/$15), and Luna ($1/$6). According to OpenAI, Sol achieves an 80-point score on the Artificial Analysis Coding Agent Index, 2.8 points above Anthropic's Fable 5, while using less than half the output tokens and costing one-third less.
Meta launches Muse Spark 1.1 coding model at $1.25/$4.25 per million tokens
Meta publicly released Muse Spark 1.1, a multimodal AI model designed for agentic coding workflows. The model is priced at $1.25 per million input tokens and $4.25 per million output tokens, positioning it slightly above Anthropic's Claude Haiku 4.5 and OpenAI's GPT-5.6 Luna.
OpenAI releases Sol model without clear government approval process, experts say
OpenAI has released its latest advanced model, Sol, for public access after government review, but researchers and industry figures say the approval process remains opaque. The model is considered comparable to Anthropic's Fable, which was briefly banned from public access, yet details of how either model received clearance are unclear.
OpenAI Releases GPT-5.6 Luna: $1/$6 Per 1M Tokens With 1M Context Window
OpenAI has released GPT-5.6 Luna, a fast and cost-efficient model in its GPT-5.6 series. The model features a 1 million token context window and is priced at $1 per 1M input tokens and $6 per 1M output tokens, with a knowledge cutoff of February 2026.
Comments
Loading...