Head-to-Head Model Comparison

Devstral 2 vs Qwen3-Coder 480B-A35B Instruct

Benchmarks, API Token Pricing, Context Window & Speed Comparison

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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Devstral 2 vs Qwen3-Coder 480B-A35B Instruct: Benchmarks, Pricing & Speed Comparison

Mistral AI tarafından geliştirilen Devstral 2 ve Alibaba tarafından sunulan Qwen3-Coder 480B-A35B Instruct, kendi sınıflarının öne çıkan yapay zeka modelleridir. Devstral 2, 262.1K token bağlam penceresi ve 1M token başına $1.50/$4.50 fiyat sunarken; Qwen3-Coder 480B-A35B Instruct, 262.1K token bağlam penceresi ve $0.00/$0.00 fiyatla gelir. Aşağıda tüm benchmark, hız ve maliyet detaylarını inceleyebilirsiniz.

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Devstral 2

Otonom Ajan ve Araç Modeli

Mistral AI tarafından geliştirilen Devstral 2; otonom ajan iş akışları, araç çağırma (tool calling) ve çok adımlı otomasyon için tasarlanmış olup 262K bağlam penceresi, 70 token/sn hız, 56/100 zeka indeksi ve 1M token başına $1.5/$4.5 fiyat

Intelligence Index56 / 100
Input Token:

$1.50 / 1M

Output Token:

$4.50 / 1M

Context Window:

262.1K tokens

SWE-bench Verified:

58.2%

Alibaba

Qwen3-Coder 480B-A35B Instruct

Açık Ağırlıklı Temel Model

Alibaba tarafından geliştirilen Qwen3-Coder 480B-A35B Instruct; özel sunucuda kendi kendine barındırma (self-hosting), ince ayar ve tam veri egemenliği için tasarlanmış olup 262K bağlam penceresi, 52 token/sn hız, 86/100 zeka indeksi ve ücr

Intelligence Index86 / 100
Input Token:

$0.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

262.1K tokens

SWE-bench Verified:

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%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureDevstral 2Qwen3-Coder 480B-A35B Instruct
Intelligence Index
Composite reasoning & knowledge score (0-100)
5686
Provider
Mistral AIAlibaba
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 text262.1K tokens~393 A4 pages of text
Max Output Tokens
Per single request
66K16K
Throughput Speed
Tokens generated per second
70 tok/s52 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 framework
Coding
Devstral 2
+1.7% SWE-bench lead
Cost
Qwen3-Coder 480B-A35B Instruct
1.0x cheaper monthly runtime
Speed
Devstral 2
+35% faster generation
Context
Tied
262.1K tokens window

Doğrulanmış Benchmark Puanları

Official evaluation metrics verified by independent third-party research labs.

Devstral 2Qwen3-Coder 480B-A35B Instruct
SWE-bench Verified (Autonomous Coding)

Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.

58.2%vs56.5%
GPQA Diamond (Doctorate-Level Science & Math)

Challenging questions created by domain experts to test complex PhD-level reasoning.

66.5%vs70%
MMLU-Pro (Multi-task Language Understanding)

Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.

83.5%vs83%
LMSYS Chatbot Arena Elo

Crowdsourced human preference evaluation based on blind, head-to-head model battles.

1365ptsvs1355pts
Terminal-Bench (Agentic Coding & Terminal Use)

Autonomous multi-step tasks executed inside a real command-line terminal environment.

52%vsN/A
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs73%
AIME (Advanced Math Competition)

American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.

78%vsN/A
Long-Context Reasoning

Accuracy when reasoning over very large inputs that fill the model context window.

82%vsN/A
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

70 tok/s vs52 tok/s

Gecikme Süresi ve Yanıt Hızı

Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.

Time to First Token (TTFT)Lower is better
Devstral 20.52s
Qwen3-Coder 480B-A35B Instruct0.76s
Est. End-to-End Response (500 tokens)TTFT + generation time
Devstral 27.66s
Qwen3-Coder 480B-A35B Instruct10.38s

Gerçek Zamanlı Token Maliyet Simülatörü

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

100K / day
10K500K1M
30K / day
5K150K300K
50% cached
0% (Cold)50%90% (Warm)
Devstral 2 Monthly API Bill
$6.82 / month
$1.5/1M in · $4.5/1M out
Qwen3-Coder 480B-A35B Instruct Monthly API Bill
$0.00 / month
$0/1M in · $0/1M out
Qwen3-Coder 480B-A35B Instruct saves approximately $6.82 / month (100%) under this workload.1.0x Savings

Devstral 2 · Strengths & Key Advantages

  • 262K bağlam penceresi ve yanıt başına maksimum 66K çıktı tokenı kapasitesi (SWE-bench Verified 58.2% · GPQA Diamond 66.5%)
  • Sadece 520 ms ilk token gecikmesi (TTFT) ile saniyede 70 token yüksek üretim hızı
  • vLLM, SGLang veya Ollama üzerinden yerel GPU sunucularında barındırılabilen açık ağırlıklı mimari (123B)
Considerations & Trade-offs
  • Tam hassasiyette yerel GPU çıkarımı için yeterli VRAM kapasitesine sahip donanım altyapısı gerektirir
  • Çok karmaşık akademik ve bilimsel çıkarımlarda üst düzey ağır akıl yürütme modelleri daha derin sonuçlar verebilir

Qwen3-Coder 480B-A35B Instruct · Strengths & Key Advantages

  • 262K bağlam penceresi ve yanıt başına maksimum 16K çıktı tokenı kapasitesi (SWE-bench Verified 56.5% · GPQA Diamond 70%)
  • Sadece 760 ms ilk token gecikmesi (TTFT) ile saniyede 52 token yüksek üretim hızı
  • vLLM, SGLang veya Ollama üzerinden yerel GPU sunucularında barındırılabilen açık ağırlıklı mimari (480B total (35B MoE))
Considerations & Trade-offs
  • Tam hassasiyette yerel GPU çıkarımı için yeterli VRAM kapasitesine sahip donanım altyapısı gerektirir
  • Çok karmaşık akademik ve bilimsel çıkarımlarda üst düzey ağır akıl yürütme modelleri daha derin sonuçlar verebilir

Token Use & Task Economics

Estimated cost and token consumption to complete one representative agentic task.

MetricDevstral 2Qwen3-Coder 480B-A35B Instruct
Cost per Task
Estimated USD to finish one task
$0.65$0.00
Output Tokens / Task
Tokens generated per task
42K25K
Reasoning Tokens / Task
Thinking tokens burned per task
20K9K

Teknik Özellikler

Architecture, release timeline, capabilities, and modalities.

FeatureDevstral 2Qwen3-Coder 480B-A35B Instruct
Official API Model ID (SDK)devstral-2-latestqwen3-coder-480b-a35b-instruct
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date2025-122025-04
Knowledge CutoffOctober 2025March 2025
ArchitectureAdvanced Agentic Code TransformerCode-Specialized Sparse Mixture-of-Experts Transformer
Parameters123B480B 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 CloudUnlimited (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 windowFree across full context window (only KV-cache VRAM scales)
Prompt Cache Policy & TTLCached input at $0.35/1M tokensAutomatic prefix KV-caching in vLLM / SGLang (0 cost)
Computer Use / GUI AgentAPI / 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 CallingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON SchemaNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & SandboxSupported via external Tavily/Exa Search & E2B/Docker Sandbox toolsSupported via external Tavily/Exa Search & E2B/Docker Sandbox tools
Official Fine-Tuning SupportFull 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 BillingText BPE (~4 chars/token)Text BPE (~4 chars/token)
Quantization & Min GPU VRAMBF16 / 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 ClassificationOpen-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 Control100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control
Input Modalitiestexttext
Output Modalitiestexttext

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

Hem Devstral 2 (otonom ajan iş akışları, araç çağırma (tool calling) ve çok adımlı otomasyon, kurumsal RAG mimarileri ve ölçeklenebilir üretim API entegrasyonları için idealdir.) hem de Qwen3-Coder 480B-A35B Instruct (özel sunucuda kendi kendine barındırma (self-hosting), ince ayar ve tam veri egemenliği, kurumsal RAG mimarileri ve ölçeklenebilir üretim API entegrasyonları için idealdir.) güçlü üretim seçenekleridir: Qwen3-Coder 480B-A35B Instruct karmaşık akıl yürütme ve kodlama testlerinde öne çıkarken, Devstral 2 daha yüksek üretim hızı sağlar; Qwen3-Coder 480B-A35B Instruct ise yüksek hacimli API kullanımlarında daha ekonomiktir.

Sıkça Sorulan Sorular (SSS)

Kodlama ve akıl yürütme için Devstral 2 mi yoksa Qwen3-Coder 480B-A35B Instruct mi daha iyi?+

Bileşik zeka endeksi ve yazılım testlerinde Qwen3-Coder 480B-A35B Instruct önde yer alıyor. Detaylı karşılaştırma için yukarıdaki SWE-bench ve GPQA tablolarına göz atabilirsiniz.

Devstral 2 ve Qwen3-Coder 480B-A35B Instruct API fiyatları nasıl karşılaştırılır?+

Devstral 2 1M giriş/çıkış tokeni başına $1.50 / $4.50 ücretlendirilirken, Qwen3-Coder 480B-A35B Instruct $0.00 / $0.00 seviyesindedir. Karma maliyette Qwen3-Coder 480B-A35B Instruct daha avantajlıdır.

Hangi modelin bağlam penceresi daha geniş ve hızı daha yüksek?+

Devstral 2 262.1K token bağlam penceresi sunarken Qwen3-Coder 480B-A35B Instruct 262.1K token kapasiteye sahiptir. Saniyedeki token üretim hızında ise Devstral 2 öndedir.

AI Terminology & Guide
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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.

Resmi kaynaklar: Mistral AI ve Alibaba resmi API dokümantasyonu, sistem kartları ve bağımsız benchmark testleri (2026).