Devstral 2 dari Mistral AI adalah model AI canggih dengan jendela konteks 262K token serta harga API $1.5/1M token input dan $4.5/1M token output untuk pemrograman, penalaran, dan otomasi bisnis.
Technical Specifications
- Provider
- Mistral AI
- Category
- flagship
- Release Date
- 2025-12
- Batch API Discount
- 50% off async batch
- Consumer Subscription
- Free / Self-Hosted
- Reasoning Effort Control
- Configurable (Low / Med / High)
- Structured Outputs
- Yes
- Output Modalities
- text
- Official Documentation
- Visit Official Docs ↗
Data Privacy, Licensing & Deployment Governance
Official Provider Release Intelligence, API Quotas & Agentic Specs
- Official API Model ID (SDK String)
- devstral-2-latest
- Supported SDK & API Protocol
- OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
- Lifecycle & Deprecation Status
- Active GA (Guaranteed support through 2027+)
- Production Rate Limits (RPM & TPM)
- Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud
- Long-Context Pricing Tier (>128K / >200K)
- Flat rate ($1.5/1M in) across full 262K window
- Prompt Cache Write & TTL Policy
- Cached input at $0.35/1M tokens
- Computer Use & Browser GUI Agent
- API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)
- MCP & Parallel Tool Calling
- Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
- Web Search Grounding & Code Sandbox
- Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools
- Fine-Tuning & Distillation Support
- Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)
- Multimodal Tokenization Billing
- Text BPE (~4 chars/token)
- Weights Precision & Quantization
- BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0)
- Minimum GPU VRAM Requirement
- 76 GB VRAM (4-bit Quantized) · 264 GB VRAM (Native BF16)
- Supported Inference Engines
- vLLM, SGLang, Ollama, llama.cpp, TensorRT-LLM, HuggingFace TGI
- System Card & Safety Framework
- Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)
- Enterprise Compliance (SOC2 / HIPAA / ZDR)
- 100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control
Devstral 2 Cost, Context, Hardware & API Integration
For single-user chat, a $20/mo subscription caps your bill below this API volume.
Break-even point: ~81 requests/day equals $20/month.
Same Monthly Workload Cost Across Popular Reference Models
Live Prompt Paste Tokenizer & Cost Counter
Paste real system instructions, JSON schemas, or code to measure BPE token counts across tokenizers.
Hybrid Prompt Routing Cascade Simulator
Route routine queries to a fast lightweight model ($0.15/1M) and escalate only complex reasoning turns to Devstral 2:
Benchmark Scores & 6-Axis Capability Radar
- SWE-bench Verified
- 58.2%
- GPQA Diamond
- 66.5%
- MMLU-Pro
- 83.5%
- HumanEval
- 94%
- Terminal-Bench
- 52%
- AIME
- 78%
- Long-Context Reasoning
- 82%
- Chatbot Arena Elo
- 1365pts
Strengths
- Arsitektur Advanced Agentic Code Transformer mutakhir dari Mistral AI dengan dukungan konteks 262K token
- Efisiensi biaya API yang kompetitif ($1.5/1M input, $4.5/1M output) dan respons cepat
- Performa andal dalam pembuatan kode, analisis logika, serta pemahaman multibahasa
Limitations & Trade-offs
- Penggunaan konteks berukuran penuh memerlukan pengelolaan anggaran token yang cermat
- Membutuhkan perancangan prompt yang tepat untuk kasus penggunaan industri spesifik
Editorial Assessment
Devstral 2 merupakan solusi AI andal dari Mistral AI yang menyeimbangkan kapabilitas, kecepatan, dan biaya.
Best for: Otomasi perusahaan, pengembangan perangkat lunak, agen AI, dan alur kerja produksi berbasis Mistral AI
Compare Devstral 2
Frequently Asked Questions about Devstral 2
How much does the Devstral 2 API cost per 1M tokens?+
Devstral 2 by Mistral AI is priced at $1.5 per 1M input tokens and $4.5 per 1M output tokens. With prompt caching enabled, cached input tokens cost $0.35 per 1M tokens, and asynchronous Batch API requests receive a 50% discount.
Should I use a $20/month subscription or the Devstral 2 pay-as-you-go API?+
A flat $20/month consumer subscription is predictable for daily interactive chat and manual coding. However, if you are building software, running automated workflows, or sending low-to-moderate volume with prompt caching enabled, the pay-as-you-go API is typically far more cost-effective and offers higher rate limits without manual UI caps.
How many words and pages fit in Devstral 2's context window?+
Devstral 2 features a 262K tokens context window, which equals approximately 196,608 English words or ~524 standard single-spaced pages in a single prompt. Its maximum output generation per turn is 65,536 tokens.
Can I run Devstral 2 locally on my own GPU (Open Weights)?+
Yes, Devstral 2 (123B) releases open weights that can be self-hosted locally or on private cloud GPUs using vLLM, Ollama, SGLang, or llama.cpp.
Does Mistral AI train on data sent to the Devstral 2 API, and is commercial use allowed?+
100% Isolated when self-hosted on private GPUs or VPC. License tier: Permissive Open-Weights (Apache 2.0 / MIT Commercial). Full commercial ownership of generated outputs. Supported deployment channels include: Self-Hosted GPU (vLLM / Ollama), Private VPC, or Managed Serverless API.
How does Devstral 2 perform on coding and reasoning benchmarks?+
Devstral 2 achieves a composite Intelligence Index of 56/100, scoring 58.2% on SWE-bench Verified, 66.5% on GPQA Diamond, 83.5% on MMLU-Pro, and 1365 pts on Chatbot Arena Elo.
What is Devstral 2 best used for?+
Devstral 2 is best suited for: Otomasi perusahaan, pengembangan perangkat lunak, agen AI, dan alur kerja produksi berbasis Mistral AI. Assessment: Devstral 2 merupakan solusi AI andal dari Mistral AI yang menyeimbangkan kapabilitas, kecepatan, dan biaya.
Mistral AI Family Lineage, Routing Tiers & Upgrade Path
Step down to a lighter sibling for high-volume routing or step up to Mistral AI's flagship reasoning tier:
Mistral Medium 3.5
Mistral Small 4
Devstral Medium
Devstral Small
Mistral Small 3.2
Mistral Medium 3
AI Glossary & Architecture Concepts
View full glossary →Key machine learning concepts and benchmarks relevant to Devstral 2:
The basic unit of text that a language model processes, typically representing about 3 to 4 English characters or roughly 0.75 words. For example, the sentence "Artificial intelligence is fast" breaks down into about 5 tokens.
A standardized evaluation suite used to objectively measure and rank an AI model's capabilities across specific tasks — such as SWE-bench Verified for software engineering, AIME for competitive math, or MMLU for general knowledge.
The maximum number of tokens a model can consider at once — both the input it reads and the output it writes. A 1,000,000-token context window can hold roughly 750,000 English words in a single request.
An AI model trained via reinforcement learning to spend dynamic compute thinking through complex logic, math, and architectural problems before outputting a solution. Examples include OpenAI o1, o3, and DeepSeek R1.
A step-by-step reasoning technique where an AI model generates intermediate problem-solving thoughts before arriving at a final answer. Native reasoning models like OpenAI o3 and DeepSeek R1 use CoT to solve complex math and coding challenges.
The ability of a language model to recognize when an external capability is needed and output structured JSON arguments to invoke external APIs, databases, or terminal commands. The runtime executes the tool and passes results back to the model.
Benchmark scores, token prices, and rate limits evolve rapidly as AI labs release model updates. Always verify current specifications and pricing on the official provider documentation.
Sumber resmi: Mistral AI Devstral 2 Release (December 2025)↗