Devstral 2 vs Claude Sonnet 5.5
Benchmarks, API Token Pricing, Context Window & Speed Comparison
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Devstral 2 by Mistral AI and Claude Sonnet 5.5 by Anthropic represent two of the frontier AI models analyzed in our comprehensive 2026 AI benchmark and LLM comparison. In this head-to-head evaluation, we examine API token pricing, context window specifications, inference speed (tokens per second), and empirical reasoning performance. From a pure economic perspective, Devstral 2 holds a notable pricing advantage for token ingestion. On output generation, Devstral 2 is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, Claude Sonnet 5.5 provides an expanded memory horizon with 1,000K tokens. In latency-sensitive production environments, Claude Sonnet 5.5 leads in tokens-per-second throughput, making it ideal for real-time conversational agents and high-concurrency workflows. Below is the complete empirical head-to-head breakdown across cost, speed, context, and capability matrices.
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Devstral 2
Code Agent v2Second-generation open software engineering agent featuring 262K context, deep terminal agent capabilities, and hardened patch generation.
$1.50 / 1M
$4.50 / 1M
262.1K tokens
58.2%
Claude Sonnet 5.5
Mid-Tier 5.5The mainstream mid-tier flagship of late 2026, inheriting the generational advances of Opus 5.5 at standard Sonnet pricing for production engineering swarms.
$2.00 / 1M
$10.00 / 1M
1M tokens
82.9%
Key Differences at a Glance
- Devstral 2 is 1.8x cheaper for API usage (input + output tokens combined).
- Claude Sonnet 5.5 has a larger context window (1M vs 262K tokens).
- Claude Sonnet 5.5 is faster at 105 tok/s vs 70 tok/s.
- Claude Sonnet 5.5 leads on SWE-bench coding (82.9% vs 58.2%).
| Feature | Devstral 2 | Claude Sonnet 5.5 |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 56 | 78 |
Provider | Mistral AI | Anthropic |
Input Price Cost per million input tokens | $1.50 / 1M | $2.00 / 1M |
Output Price Cost per million output tokens | $4.50 / 1M | $10.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.99 / 1M | $1.54 / 1M |
Context Window Maximum input + output tokens | 262.1K tokens~393 A4 pages of text | 1M tokens~1,500 A4 pages of text |
Max Output Tokens Per single request | 66K | 128K |
Throughput Speed Tokens generated per second | 70 tok/s | 105 tok/s |
SWE-bench Verified Real-world software engineering | 58.2% | 82.9% |
GPQA Diamond Graduate-level reasoning | 66.5% | 79.4% |
Cached Input Price Prompt caching discount per 1M tokens | $0.35 / 1M | $0.20 / 1M |
Who Wins Where?
At-a-glance decision frameworkEmpirical Head-to-Head Benchmark Scores
Official evaluation metrics verified by independent third-party research labs.
Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.
Challenging questions created by domain experts to test complex PhD-level reasoning.
Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.
Crowdsourced human preference evaluation based on blind, head-to-head model battles.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.
Accuracy when reasoning over very large inputs that fill the model context window.
Tokens emitted per second during active generation streaming.
Latency & Response Time
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Real-Time Interactive Token Cost Simulator
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Devstral 2 · Strengths & Key Advantages
- Expanded 262K context window to ingest entire multi-package monorepos
- State-of-the-art 58.2% SWE-bench score for an open-weights model
- Hardened against regression loops and terminal syntax hallucination
Considerations & Trade-offs
- Substantial 123B parameter memory requirement for local execution
- API token costs are moderately high for intensive multi-turn loops
Claude Sonnet 5.5 · Strengths & Key Advantages
- Incredible 82.9% SWE-bench Verified score at everyday $3/$15 API rates
- Full 1M token context with high-speed 105 tokens/sec generation
- Streamlined multi-agent coordination with low latency
Considerations & Trade-offs
- Slightly behind Opus 5.5 on extremely dense multi-hour scientific theorems
- Cached prompt overhead during massive 1M token updates
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Devstral 2 | Claude Sonnet 5.5 |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.65 | $3.29 |
Output Tokens / Task Tokens generated per task | 42K | 72K |
Reasoning Tokens / Task Thinking tokens burned per task | 20K | 37K |
Technical Specifications
Architecture, release timeline, capabilities, and modalities.
| Feature | Devstral 2 | Claude Sonnet 5.5 |
|---|---|---|
| Official API Model ID (SDK) | devstral-2-latest | claude-sonnet-5-5-20260901 |
| API Protocol | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI | Anthropic Messages API + AWS Bedrock + Vertex AI |
| Release Date | 2025-12 | 2026-09 |
| Knowledge Cutoff | October 2025 | June 2026 |
| Architecture | Advanced Agentic Code Transformer | Adaptive Frontier Multimodal Transformer |
| Parameters | 123B | Confidential |
| Enterprise Rate Limits (RPM / TPM) | Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud | 4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 4,000,000 – 10,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($1.5/1M in) across full 262K window | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens |
| Prompt Cache Policy & TTL | Cached input at $0.35/1M tokens | $0.2/1M cached read (90% off); 5-min default & 1-hour extended TTL |
| Computer Use / GUI Agent | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) | Supported (Screen coordinate grounding, browser & desktop GUI action loops) |
| MCP & Parallel Tool Calling | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema |
| Web Search Grounding & Sandbox | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools | Native Web Search Citations + Code Execution Tool + MCP Connectors |
| Official Fine-Tuning Support | Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory) | Custom Model Tuning via Amazon Bedrock & Prompt Distillation |
| Multimodal Token Billing | Text BPE (~4 chars/token) | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) |
| Quantization & Min GPU VRAM | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 76 GB VRAM (4-bit Quantized) · 264 GB VRAM (Native BF16) | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) |
| Safety & Frontier Classification | Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma) | Anthropic RSP ASL-2 / ASL-3 Constitutional Safety Evaluated |
| Enterprise Compliance (ZDR/HIPAA/SOC2) | 100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier |
| Input Modalities | text | text, vision |
| Output Modalities | text | text |
Devstral 2 vs Claude Sonnet 5.5: Quick Answers
Which is more intelligent, Devstral 2 or Claude Sonnet 5.5?
Claude Sonnet 5.5 is more intelligent. It scores 78 compared with 56 on the composite Intelligence Index.
Which model is faster?
Claude Sonnet 5.5 is faster, generating 105 tokens per second compared with 70 tokens per second.
Which model is cheaper to run?
Devstral 2 is cheaper at $0.99 per 1M tokens blended, compared with $1.54 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Devstral 2 has lower latency, with a time to first token of 0.52s compared with 0.55s.
Which model has a larger context window?
Claude Sonnet 5.5 has a larger context window, supporting 1M tokens compared with 262.1K tokens.
Verdict
Verdict & Model Selection Recommendation: Choose Devstral 2 if your priority is Whole-repository migrations, autonomous developer agents, and complex architecture refactors. Its performance in demanding tasks justifies its operational token cost. Choose Claude Sonnet 5.5 if your workflow prioritizes Daily production development, agentic workflows, IDE integrations, and automated code review. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
Frequently asked questions
How does Devstral 2 compare to Claude Sonnet 5.5 in API token pricing and cost per token?+
Devstral 2 costs $1.50 per 1M input tokens and $4.50 per 1M output tokens, whereas Claude Sonnet 5.5 costs $2.00 input and $10.00 output. Overall, Devstral 2 is the more cost-effective model for high-volume API pipelines. Both models support prompt caching discounts of up to 90% for repeated prompt prefixes.
Which model has a larger context window: Devstral 2 or Claude Sonnet 5.5?+
Devstral 2 supports a context window of 262K tokens (~197k words), while Claude Sonnet 5.5 supports 1,000K tokens (~750k words). Therefore, Claude Sonnet 5.5 can process more textual data and document context in a single prompt.
Which AI model is better for software engineering and coding: Devstral 2 or Claude Sonnet 5.5?+
Devstral 2 scores 58.2% on SWE-bench Verified while Claude Sonnet 5.5 scores 82.9%. For autonomous software engineering and multi-file debugging, Claude Sonnet 5.5 holds the verified benchmark lead.
What is the difference in reasoning capability and extended thinking between Devstral 2 and Claude Sonnet 5.5?+
Devstral 2 features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, Claude Sonnet 5.5 provides chain-of-thought reasoning depth for complex math and science.
How does inference speed (tokens per second) compare between Devstral 2 and Claude Sonnet 5.5?+
Devstral 2 generates approximately 70 tokens per second, while Claude Sonnet 5.5 delivers 105 tokens per second. In latency-sensitive production environments, Claude Sonnet 5.5 provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining Devstral 2 and Claude Sonnet 5.5 to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Devstral 2 to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Claude Sonnet 5.5. This tiered routing pattern cuts overall API bills by up to 70%.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
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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.
Sources: GetInfoUs Independent AI Benchmarks & Official API Specs