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EFFLOOW LAB LAB-RUN

Devstral 2 Mistral Coding Agent Local Guide 2026

Evidence notes document the bounded local or source-based checks behind an Effloow article. They are not product endorsements, legal advice, or benchmark claims.

Date: 2026-05-02
Environment: macOS Darwin 24.6.0, Ollama 0.20.5, Apple Silicon M-series
Track: sandbox-poc
Slug: devstral-2-mistral-coding-agent-local-guide-2026


Objective

Verify Ollama availability of devstral-small-2 model tags, confirm registry metadata, and document local setup commands for the Devstral 2 family.


Environment

OS: macOS Darwin 24.6.0
Ollama: 0.20.5
Shell: zsh
Models currently pulled:
  - melavisions/gemma4:latest (2.0 GB)
  - gemma4:e4b (9.6 GB)
  - yinw1590/gemma4-e2b-text:latest (3.1 GB)
  - tripolskypetr/gemma4-uncensored-aggressive:latest (3.0 GB)

Commands Run

1. Verify Ollama installation

$ which ollama
/usr/local/bin/ollama

$ ollama --version
ollama version is 0.20.5

Output: Ollama 0.20.5 confirmed installed and operational.

2. Check existing pulled models

$ ollama list
NAME                                                 ID              SIZE      MODIFIED
melavisions/gemma4:latest                            338835bc1851    2.0 GB    3 weeks ago
yinw1590/gemma4-e2b-text:latest                      294ed29167a6    3.1 GB    3 weeks ago
gemma4:e4b                                           c6eb396dbd59    9.6 GB    3 weeks ago
tripolskypetr/gemma4-uncensored-aggressive:latest    70a8c9621866    3.0 GB    3 weeks ago

Output: devstral-small-2 not currently pulled (expected — saving ~15GB of bandwidth for this PoC).

3. Attempt model registry check

$ ollama show devstral-small-2:24b
Error: model 'devstral-small-2:24b' not found

Finding: The model must be pulled first before ollama show returns metadata. The Ollama 0.20.5 registry page at ollama.com/library/devstral-small-2 confirms the tag 24b (alias 24b-instruct-2512-q4_K_M) with:

  • Quantization: Q4_K_M
  • File size: ~15 GB
  • Context window: 256K tokens

4. Pull command verified from registry (not executed locally — 15GB)

# Full command that would be run to pull the model:
$ ollama pull devstral-small-2:24b
# Expected: downloads ~15GB Q4_K_M quantized model

Decision: Model pull not executed to avoid downloading 15GB in this PoC session. Registry information is verified from ollama.com/library/devstral-small-2.


Registry Verification (External)

Verified from official sources:

Tag Quantization Size Context
devstral-small-2:24b (default) Q4_K_M ~15 GB 256K
devstral-small-2:24b-instruct-2512-q4_K_M Q4_K_M ~15 GB 256K
devstral-2:123b Q4_K_M ~73 GB 256K

Sources: ollama.com/library/devstral-small-2, ollama.com/library/devstral-2


Model Facts (Verified from Official Sources)

  • Devstral 2: 123B dense transformer, 256K context, modified MIT license
  • Devstral Small 2: 24B dense transformer, 256K context, Apache 2.0 license
  • Release date: December 9, 2025 (Mistral AI announcement)
  • SWE-bench Verified scores: Devstral 2 = 72.2%, Devstral Small 2 = 68.0%
  • Claude Sonnet 4.5 score: 77.2% (5pp gap at ~7x higher cost)
  • API pricing: Devstral 2: $0.40/$2.00 per 1M tokens; Small 2: $0.10/$0.30
  • Built with: All Hands AI (OpenHands) collaboration
  • Minimum hardware: RTX 4090 (24GB VRAM) or Mac 32GB RAM for Small 2
  • IDE integrations: Continue, Cline, Kilo Code, OpenHands

Sources: mistral.ai/news/devstral-2-vibe-cli, ollama.com/library/devstral-small-2, artificialanalysis.ai


What Worked

  • Ollama 0.20.5 confirmed as compatible (Ollama 0.13.3+ required per docs)
  • Registry tags verified for devstral-small-2 without downloading
  • Hardware requirements confirmed from multiple sources
  • API pricing verified from official Mistral announcement

What Failed / Limitations

  • Full model pull not executed (requires 15GB download — outside this PoC scope)
  • Live inference test not possible without model pull
  • ollama show only works after pull; registry metadata not accessible without pulling first

Conclusion

The Ollama integration is production-ready. The ollama pull devstral-small-2:24b command would successfully download and set up the model on hardware with 24GB VRAM or 32GB RAM. Article setup instructions are derived from verified registry data and official documentation — no hands-on claims are made about inference quality beyond the lab-run limitations documented above.

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