Devstral 2 vs Qwen3-Coder 480B-A35B Instruct
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Devstral 2 by Mistral AI and Qwen3-Coder 480B-A35B Instruct by Alibaba 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, Qwen3-Coder 480B-A35B Instruct holds a notable pricing advantage for token ingestion. On output generation, Qwen3-Coder 480B-A35B Instruct is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, both models provide an identical memory horizon with 262K tokens. In latency-sensitive production environments, Devstral 2 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
Açık Ağırlıklı ModelMistral AI tarafından geliştirilen Devstral 2, 262K token bağlam penceresi ve 1M girdi başına $1.5, 1M çıktı başına $4.5 API fiyatlandırmasıyla yazılım geliştirme, analiz ve kurumsal otomasyon için tasarlanmıştır.
$1.50 / 1M
$4.50 / 1M
262.1K tokens
58.2%
Qwen3-Coder 480B-A35B Instruct
Açık Ağırlıklı ModelAlibaba tarafından geliştirilen Qwen3-Coder 480B-A35B Instruct, 262K token bağlam penceresi ve 1M girdi başına $0, 1M çıktı başına $0 API fiyatlandırmasıyla yazılım geliştirme, analiz ve kurumsal otomasyon için tasarlanmıştır.
$0.00 / 1M
$0.00 / 1M
262.1K tokens
56.5%
Bir Bakışta Temel Farklar
- Qwen3-Coder 480B-A35B Instruct is 1.0x cheaper for API usage (input + output tokens combined).
- Devstral 2 is faster at 70 tok/s vs 52 tok/s.
- Devstral 2 leads on SWE-bench coding (58.2% vs 56.5%).
| Feature | Devstral 2 | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 56 | 86 |
Provider | Mistral AI | Alibaba |
Input Price Cost per million input tokens | $1.50 / 1M | $0.00 / 1M |
Output Price Cost per million output tokens | $4.50 / 1M | $0.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.99 / 1M | $0.00 / 1M |
Context Window Maximum input + output tokens | 262.1K tokens~393 A4 pages of text | 262.1K tokens~393 A4 pages of text |
Max Output Tokens Per single request | 66K | 16K |
Throughput Speed Tokens generated per second | 70 tok/s | 52 tok/s |
SWE-bench Verified Real-world software engineering | 58.2% | 56.5% |
GPQA Diamond Graduate-level reasoning | 66.5% | 70% |
Cached Input Price Prompt caching discount per 1M tokens | $0.35 / 1M | $0.00 / 1M |
Hangi Alanda Kim Kazanıyor?
At-a-glance decision frameworkDoğrulanmış Benchmark Puanları
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.
Contamination-free competitive programming problems collected continuously over time.
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.
Gecikme Süresi ve Yanıt Hızı
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Gerçek Zamanlı Token Maliyet Simülatörü
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Devstral 2 · Strengths & Key Advantages
- Mistral AI imzalı gelişmiş Advanced Agentic Code Transformer mimarisi ve 262K token bağlam kapasitesi
- Dengeli API maliyeti ($1.5/1M girdi, $4.5/1M çıktı) ve yüksek yanıt hızı
- Kod üretimi, mantıksal çıkarım ve çok dilli görevlerde güçlü kıyaslama (benchmark) sonuçları
Considerations & Trade-offs
- Çok uzun bağlamlı sorgularda token maliyetlerinin dikkatli yönetilmesi gerekir
- Alan bazlı özel iş akışlarında en yüksek verim için doğru istem (prompt) tasarımı önerilir
Qwen3-Coder 480B-A35B Instruct · Strengths & Key Advantages
- Alibaba imzalı gelişmiş Code-Specialized Sparse Mixture-of-Experts Transformer mimarisi ve 262K token bağlam kapasitesi
- Dengeli API maliyeti ($0/1M girdi, $0/1M çıktı) ve yüksek yanıt hızı
- Kod üretimi, mantıksal çıkarım ve çok dilli görevlerde güçlü kıyaslama (benchmark) sonuçları
Considerations & Trade-offs
- Çok uzun bağlamlı sorgularda token maliyetlerinin dikkatli yönetilmesi gerekir
- Alan bazlı özel iş akışlarında en yüksek verim için doğru istem (prompt) tasarımı önerilir
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Devstral 2 | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.65 | $0.00 |
Output Tokens / Task Tokens generated per task | 42K | 25K |
Reasoning Tokens / Task Thinking tokens burned per task | 20K | 9K |
Teknik Özellikler
Architecture, release timeline, capabilities, and modalities.
| Feature | Devstral 2 | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| Official API Model ID (SDK) | devstral-2-latest | qwen3-coder-480b-a35b-instruct |
| API Protocol | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI |
| Release Date | 2025-12 | 2025-04 |
| Knowledge Cutoff | October 2025 | March 2025 |
| Architecture | Advanced Agentic Code Transformer | Code-Specialized Sparse Mixture-of-Experts Transformer |
| Parameters | 123B | 480B total (35B active MoE) |
| Enterprise Rate Limits (RPM / TPM) | Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud | Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud |
| Long-Context Tier (>128K/200K) | Flat rate ($1.5/1M in) across full 262K window | Free across full context window (only KV-cache VRAM scales) |
| Prompt Cache Policy & TTL | Cached input at $0.35/1M tokens | Automatic prefix KV-caching in vLLM / SGLang (0 cost) |
| Computer Use / GUI Agent | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) | 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 | 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 | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools |
| Official Fine-Tuning Support | Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory) | Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory) |
| Multimodal Token Billing | Text BPE (~4 chars/token) | Text BPE (~4 chars/token) |
| 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) | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 298 GB VRAM (4-bit Quantized) · 1032 GB VRAM (Native BF16) |
| Safety & Frontier Classification | Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma) | Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma) |
| Enterprise Compliance (ZDR/HIPAA/SOC2) | 100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control | 100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control |
| Input Modalities | text | text |
| Output Modalities | text | text |
Devstral 2 vs Qwen3-Coder 480B-A35B Instruct: Hızlı Yanıtlar (SSS)
Which is more intelligent, Devstral 2 or Qwen3-Coder 480B-A35B Instruct?
Qwen3-Coder 480B-A35B Instruct is more intelligent. It scores 86 compared with 56 on the composite Intelligence Index.
Which model is faster?
Devstral 2 is faster, generating 70 tokens per second compared with 52 tokens per second.
Which model is cheaper to run?
Qwen3-Coder 480B-A35B Instruct is cheaper at $0.00 per 1M tokens blended, compared with $0.99 (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 0.76s.
Sonuç
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 Qwen3-Coder 480B-A35B Instruct if your workflow prioritizes Enterprise software development agents, automated code migration, and security vulnerability auditing. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
Sıkça Sorulan Sorular (SSS)
How does Devstral 2 compare to Qwen3-Coder 480B-A35B Instruct 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 Qwen3-Coder 480B-A35B Instruct costs $0.00 input and $0.00 output. Overall, Qwen3-Coder 480B-A35B Instruct 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 Qwen3-Coder 480B-A35B Instruct?+
Both Devstral 2 and Qwen3-Coder 480B-A35B Instruct offer an identical context window of 262K tokens (~197k words). Both architectures provide equal capacity for large document ingestion, multi-file codebases, and extended multi-turn conversation histories.
Which AI model is better for software engineering and coding: Devstral 2 or Qwen3-Coder 480B-A35B Instruct?+
Devstral 2 scores 58.2% on SWE-bench Verified while Qwen3-Coder 480B-A35B Instruct scores 56.5%. For autonomous software engineering and multi-file debugging, Devstral 2 holds the verified benchmark lead.
What is the difference in reasoning capability and extended thinking between Devstral 2 and Qwen3-Coder 480B-A35B Instruct?+
Devstral 2 features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, Qwen3-Coder 480B-A35B Instruct provides chain-of-thought reasoning depth for complex math and science.
How does inference speed (tokens per second) compare between Devstral 2 and Qwen3-Coder 480B-A35B Instruct?+
Devstral 2 generates approximately 70 tokens per second, while Qwen3-Coder 480B-A35B Instruct delivers 52 tokens per second. In latency-sensitive production environments, Devstral 2 provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining Devstral 2 and Qwen3-Coder 480B-A35B Instruct to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Qwen3-Coder 480B-A35B Instruct to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Devstral 2. 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.
Related reading
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- GPT-5.2 Codex vs Devstral 2: Benchmarks, Pricing & Speed ComparisonKarşılaştır
- GPT-5-Codex vs Qwen3-Coder 480B-A35B Instruct: Benchmarks, Pricing & Speed ComparisonKarşılaştır
- Qwen3-Coder 480B-A35B Instruct vs Claude 3.7 Sonnet: Benchmarks, Pricing & Speed ComparisonKarşılaştır
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.
Resmi kaynaklar: GetInfoUs Independent AI Benchmarks & Official API Specs