Head-to-Head Model Comparison

Mistral Medium 3.5 vs Claude Sonnet 5.5

Benchmarks, API Token Pricing, Context Window & Speed Comparison

GetInfoUs araştırma ekibi tarafından incelendiSon inceleme: October 2026Yayın ilkeleri

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Mistral Medium 3.5Profile

Claude Sonnet 5.5Profile

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Mistral AI

Mistral Medium 3.5

Açık Ağırlıklı Temel Model

Mistral AI tarafından geliştirilen Mistral Medium 3.5; özel sunucuda kendi kendine barındırma (self-hosting), ince ayar ve tam veri egemenliği için tasarlanmış olup 262K bağlam penceresi, 90 token/sn hız, 55/100 zeka indeksi ve 1M token baş

Intelligence Index55 / 100

Input Token:

$0.40 / 1M

Output Token:

$2.00 / 1M

Context Window:

262.1K tokens

SWE-bench Verified:

54%

Anthropic

Claude Sonnet 5.5

Amiral Gemisi Öncü Model

Anthropic tarafından geliştirilen Claude Sonnet 5.5; öncü kurumsal akıl yürütme, yazılım geliştirme ve üretim ölçekli AI iş akışları için tasarlanmış olup 1M bağlam penceresi, 105 token/sn hız, 78/100 zeka indeksi ve 1M token başına $2/$10

Intelligence Index78 / 100

Input Token:

$2.00 / 1M

Output Token:

$10.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

82.9%

Bir Bakışta Temel Farklar

Mistral Medium 3.5 is 4.8x 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 90 tok/s.
Claude Sonnet 5.5 leads on SWE-bench coding (82.9% vs 54.0%).

Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →

Feature	Mistral Medium 3.5	Claude Sonnet 5.5
Intelligence Index Composite reasoning & knowledge score (0-100)	55	78
Provider	Mistral AI	Anthropic
Input Price Cost per million input tokens	$0.40 / 1M	$2.00 / 1M
Output Price Cost per million output tokens	$2.00 / 1M	$10.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$0.35 / 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	33K	128K
Throughput Speed Tokens generated per second	90 tok/s	105 tok/s
SWE-bench Verified Real-world software engineering	54%	82.9%
GPQA Diamond Graduate-level reasoning	68%	79.4%
Cached Input Price Prompt caching discount per 1M tokens	$0.10 / 1M	$0.20 / 1M

Hangi Alanda Kim Kazanıyor?

At-a-glance decision framework

Coding

Claude Sonnet 5.5

+28.9% SWE-bench lead

Cost

Mistral Medium 3.5

4.8x cheaper monthly runtime

Speed

Claude Sonnet 5.5

+17% faster generation

Context

Claude Sonnet 5.5

1M tokens window

Doğrulanmış Benchmark Puanları

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

Mistral Medium 3.5Claude Sonnet 5.5

SWE-bench Verified (Autonomous Coding)

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

54%vs82.9%

GPQA Diamond (Doctorate-Level Science & Math)

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

68%vs79.4%

MMLU-Pro (Multi-task Language Understanding)

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

84.5%vs90.1%

LMSYS Chatbot Arena Elo

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

1370ptsvs1490pts

Terminal-Bench (Agentic Coding & Terminal Use)

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

46%vs58.9%

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.

85%vsN/A

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

90 tok/s vs105 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

Mistral Medium 3.50.45s

Claude Sonnet 5.50.55s

Est. End-to-End Response (500 tokens)TTFT + generation time

Mistral Medium 3.56.01s

Claude Sonnet 5.55.31s

Gerçek Zamanlı Token Maliyet Simülatörü

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

Daily Input Tokens100K / day

10K500K1M

Daily Output Tokens30K / day

5K150K300K

Prompt Cache Hit Ratio50% cached

0% (Cold)50%90% (Warm)

Mistral Medium 3.5 Monthly API Bill

$2.55 / month

$0.4/1M in · $2/1M out

Claude Sonnet 5.5 Monthly API Bill

$12.30 / month

$2/1M in · $10/1M out

Mistral Medium 3.5 saves approximately $9.75 / month (79%) under this workload.4.8x Savings

Mistral Medium 3.5 · Strengths & Key Advantages

262K bağlam penceresi ve yanıt başına maksimum 33K çıktı tokenı kapasitesi (SWE-bench Verified 54% · GPQA Diamond 68%)
Sadece 450 ms ilk token gecikmesi (TTFT) ile saniyede 90 token yüksek üretim hızı
vLLM, SGLang veya Ollama üzerinden yerel GPU sunucularında barındırılabilen açık ağırlıklı mimari (Confidential (~80B 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

Claude Sonnet 5.5 · Strengths & Key Advantages

1M bağlam penceresi ve yanıt başına maksimum 128K çıktı tokenı kapasitesi (SWE-bench Verified 82.9% · GPQA Diamond 79.4%)
Sadece 550 ms ilk token gecikmesi (TTFT) ile saniyede 105 token yüksek üretim hızı
İstem önbellekleme (Prompt Caching), araç çağırma ve yapılandırılmış JSON çıktısını destekleyen rekabetçi API ekonomisi (1M token başına $2/$10 fiyatlandırma)

Considerations & Trade-offs

Kapalı ağırlıklı bulut modelidir; çevrimdışı yerel sunuculara indirilerek çalıştırılamaz
Yüksek hacimli üretim trafiğinde maliyetleri optimize etmek için Prompt Caching ve Batch API kullanımı önerilir

Token Use & Task Economics

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

Metric	Mistral Medium 3.5	Claude Sonnet 5.5
Cost per Task Estimated USD to finish one task	$0.38	$3.29
Output Tokens / Task Tokens generated per task	38K	72K
Reasoning Tokens / Task Thinking tokens burned per task	18K	37K

Teknik Özellikler

Architecture, release timeline, capabilities, and modalities.

Feature	Mistral Medium 3.5	Claude Sonnet 5.5
Official API Model ID (SDK)	mistral-medium-3-5-latest	claude-sonnet-5-5-20260901
API Protocol	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI	Anthropic Messages API + AWS Bedrock + Vertex AI
Release Date	2026-04	2026-09
Knowledge Cutoff	February 2026	June 2026
Architecture	Enterprise Hybrid Reasoning MoE	Adaptive Frontier Multimodal Transformer
Parameters	Confidential (~80B MoE)	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 ($0.4/1M 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 $0.1/1M 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) · Vision (~258–765 tokens per image tile)	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) · 50 GB VRAM (4-bit Quantized) · 172 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, vision	text, vision
Output Modalities	text	text

Mistral Medium 3.5 vs Claude Sonnet 5.5: Hızlı Yanıtlar (SSS)

Which is more intelligent, Mistral Medium 3.5 or Claude Sonnet 5.5?

Claude Sonnet 5.5 is more intelligent. It scores 78 compared with 55 on the composite Intelligence Index.

Which model is faster?

Claude Sonnet 5.5 is faster, generating 105 tokens per second compared with 90 tokens per second.

Which model is cheaper to run?

Mistral Medium 3.5 is cheaper at $0.35 per 1M tokens blended, compared with $1.54 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Mistral Medium 3.5 has lower latency, with a time to first token of 0.45s 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.

Sonuç

Hem Mistral Medium 3.5 (özel sunucuda kendi kendine barındırma (self-hosting), ince ayar ve tam veri egemenliği, kurumsal RAG mimarileri ve ölçeklenebilir üretim API entegrasyonları için idealdir.) hem de Claude Sonnet 5.5 (öncü kurumsal akıl yürütme, yazılım geliştirme ve üretim ölçekli AI iş akışları, kurumsal RAG mimarileri ve ölçeklenebilir üretim API entegrasyonları için idealdir.) güçlü üretim seçenekleridir: Claude Sonnet 5.5 karmaşık akıl yürütme ve kodlama testlerinde öne çıkarken, Claude Sonnet 5.5 daha yüksek üretim hızı sağlar; Mistral Medium 3.5 ise yüksek hacimli API kullanımlarında daha ekonomiktir.

Sıkça Sorulan Sorular (SSS)

Kodlama ve akıl yürütme için Mistral Medium 3.5 mi yoksa Claude Sonnet 5.5 mi daha iyi?+

Bileşik zeka endeksi ve yazılım testlerinde Claude Sonnet 5.5 önde yer alıyor. Detaylı karşılaştırma için yukarıdaki SWE-bench ve GPQA tablolarına göz atabilirsiniz.

Mistral Medium 3.5 ve Claude Sonnet 5.5 API fiyatları nasıl karşılaştırılır?+

Mistral Medium 3.5 1M giriş/çıkış tokeni başına $0.40 / $2.00 ücretlendirilirken, Claude Sonnet 5.5 $2.00 / $10.00 seviyesindedir. Karma maliyette Mistral Medium 3.5 daha avantajlıdır.

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

Mistral Medium 3.5 262.1K token bağlam penceresi sunarken Claude Sonnet 5.5 1M token kapasiteye sahiptir. Saniyedeki token üretim hızında ise Claude Sonnet 5.5 öndedir.

AI Terminology & Guide

Explore Glossary →

Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.

Tokens & Pricing Context Window AI Benchmarks Reasoning Models Tool Calling Model Context Protocol (MCP)

Mistral Medium 3.5 vs Claude Sonnet 5.5

İstediğiniz Modelleri Seçin ve Karşılaştırın

Mistral Medium 3.5

Claude Sonnet 5.5

Hangi Alanda Kim Kazanıyor?

Doğrulanmış Benchmark Puanları

Gecikme Süresi ve Yanıt Hızı

Gerçek Zamanlı Token Maliyet Simülatörü

Mistral Medium 3.5 · Strengths & Key Advantages

Considerations & Trade-offs

Claude Sonnet 5.5 · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Teknik Özellikler

Mistral Medium 3.5 vs Claude Sonnet 5.5: Hızlı Yanıtlar (SSS)

Sonuç

Sıkça Sorulan Sorular (SSS)

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