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Head-to-Head Model Comparison

Mistral Medium 3.5 vs Claude Opus 5.5

Benchmarks, API Token Pricing, Context Window & Speed Comparison

تمت المراجعة بواسطة فريق أبحاث GetInfoUsآخر مراجعة: October 2026السياسة التحريرية
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Mistral AIAnthropicflagshipflagship

Compare Mistral Medium 3.5 by Mistral AI against Claude Opus 5.5 by Anthropic across real-world coding, reasoning, token economics, and latency.

مقارنة مباشرة (VS)

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Mistral AI

Mistral Medium 3.5

نموذج أساسي مفتوح الأوزان

نموذج Mistral Medium 3.5 من Mistral AI مصمم خصيصاً لـالاستضافة الذاتية على الخوادم الخاصة والضبط الدقيق والسيادة الكاملة على البيانات، حيث يوفر نافذة سياق بسعة 262K وسرعة 90 رمز/ثانية ومؤشر ذكاء 55/100 (بتكلفة $0.4/$2 لكل مليون رمز).

Intelligence Index55 / 100
Input Token:

$0.40 / 1M

Output Token:

$2.00 / 1M

Context Window:

262.1K tokens

SWE-bench Verified:

54%

Anthropic

Claude Opus 5.5

نموذج رائد متقدم

نموذج Claude Opus 5.5 من Anthropic مصمم خصيصاً لـالاستدلال المؤسسي المتقدم وهندسة البرمجيات وتطبيقات الإنتاج واسعة النطاق، حيث يوفر نافذة سياق بسعة 1M وسرعة 78 رمز/ثانية ومؤشر ذكاء 94/100 (بتكلفة $4/$20 لكل مليون رمز).

Intelligence Index94 / 100
Input Token:

$4.00 / 1M

Output Token:

$20.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

84.6%

أهم الفروقات في لمحة

  • Mistral Medium 3.5 is 9.6x cheaper for API usage (input + output tokens combined).
  • Claude Opus 5.5 has a larger context window (1M vs 262K tokens).
  • Mistral Medium 3.5 is faster at 90 tok/s vs 78 tok/s.
  • Claude Opus 5.5 leads on SWE-bench coding (84.6% vs 54.0%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureMistral Medium 3.5Claude Opus 5.5
Intelligence Index
Composite reasoning & knowledge score (0-100)
5594
Provider
Mistral AIAnthropic
Input Price
Cost per million input tokens
$0.40 / 1M$4.00 / 1M
Output Price
Cost per million output tokens
$2.00 / 1M$20.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.35 / 1M$3.08 / 1M
Context Window
Maximum input + output tokens
262.1K tokens~393 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
33K128K
Throughput Speed
Tokens generated per second
90 tok/s78 tok/s
SWE-bench Verified
Real-world software engineering
54%84.6%
GPQA Diamond
Graduate-level reasoning
68%82.3%
Cached Input Price
Prompt caching discount per 1M tokens
$0.10 / 1M$0.40 / 1M

من يتفوق في كل مجال؟

At-a-glance decision framework
Coding
Claude Opus 5.5
+30.6% SWE-bench lead
Cost
Mistral Medium 3.5
9.6x cheaper monthly runtime
Speed
Mistral Medium 3.5
+15% faster generation
Context
Claude Opus 5.5
1M tokens window

نتائج الاختبارات المعيارية الموثقة

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

Mistral Medium 3.5Claude Opus 5.5
SWE-bench Verified (Autonomous Coding)

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

54%vs84.6%
GPQA Diamond (Doctorate-Level Science & Math)

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

68%vs82.3%
MMLU-Pro (Multi-task Language Understanding)

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

84.5%vs91.5%
LMSYS Chatbot Arena Elo

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

1370ptsvs1507pts
Humanity's Last Exam (Frontier Expert Knowledge)

Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.

N/Avs19.8%
Terminal-Bench (Agentic Coding & Terminal Use)

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

46%vs66.4%
SciCode (Scientific Computing)

Research-grade coding problems drawn from real scientific and numerical workloads.

N/Avs58.7%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs83.1%
AIME (Advanced Math Competition)

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

78%vs95.4%
Long-Context Reasoning

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

85%vs92.6%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

90 tok/s vs78 tok/s

زمن الاستجابة والسرعة

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 Opus 5.51.40s
Est. End-to-End Response (500 tokens)TTFT + generation time
Mistral Medium 3.56.01s
Claude Opus 5.57.81s

محاكي تكلفة الرموز التفاعلي

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)
Mistral Medium 3.5 Monthly API Bill
$2.55 / month
$0.4/1M in · $2/1M out
Claude Opus 5.5 Monthly API Bill
$24.60 / month
$4/1M in · $20/1M out
Mistral Medium 3.5 saves approximately $22.05 / month (90%) under this workload.9.6x Savings

Mistral Medium 3.5 · Strengths & Key Advantages

  • نافذة سياق بسعة 262K وحد أقصى للمخرجات يصل إلى 33K رمز (SWE-bench Verified 54% · GPQA Diamond 68%)
  • سرعة توليد عالية تبلغ 90 رمز/ثانية مع زمن استجابة لأول رمز (TTFT) قدره 450 مللي ثانية
  • أوزان مفتوحة (Confidential (~80B MoE)) تتيح الاستضافة الذاتية محلياً أو عبر السحابة الخاصة باستخدام vLLM وOllama
Considerations & Trade-offs
  • يتطلب خوادم GPU بذاكرة VRAM كافية عند التشغيل المحلي بالدقة الكاملة
  • في المسائل البحثية فائقة التعقيد، قد تتفوق نماذج الاستدلال الثقيلة المتخصصة في عمق التحليل

Claude Opus 5.5 · Strengths & Key Advantages

  • نافذة سياق بسعة 1M وحد أقصى للمخرجات يصل إلى 128K رمز (SWE-bench Verified 84.6% · GPQA Diamond 82.3%)
  • سرعة توليد عالية تبلغ 78 رمز/ثانية مع زمن استجابة لأول رمز (TTFT) قدره 1400 مللي ثانية
  • تسعير API تنافسي (بتكلفة $4/$20 لكل مليون رمز) مع دعم التخزين المؤقت للأوامر والمخرجات المهيكلة بصيغة JSON
Considerations & Trade-offs
  • نموذج سحابي مغلق الأوزان لا يدعم تنزيل الأوزان للتشغيل المحلي المعزول عن الإنترنت
  • في حالات الاستخدام الكثيف، يُنصح بتفعيل التخزين المؤقت (Prompt Caching) وBatch API لترشيد النفقات

Token Use & Task Economics

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

MetricMistral Medium 3.5Claude Opus 5.5
Cost per Task
Estimated USD to finish one task
$0.38$3.85
Output Tokens / Task
Tokens generated per task
38K68K
Reasoning Tokens / Task
Thinking tokens burned per task
18K42K

المواصفات التقنية

Architecture, release timeline, capabilities, and modalities.

FeatureMistral Medium 3.5Claude Opus 5.5
Official API Model ID (SDK)mistral-medium-3-5-latestclaude-opus-5-5-20260901
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIAnthropic Messages API + AWS Bedrock + Vertex AI
Release Date2026-042026-09
Knowledge CutoffFebruary 2026June 2026
ArchitectureEnterprise Hybrid Reasoning MoEExtended Autonomous Hybrid Reasoning Transformer
ParametersConfidential (~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 Cloud4,000 – 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 windowStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLCached input at $0.1/1M tokens$0.4/1M cached read (90% off); 5-min default & 1-hour extended TTL
Computer Use / GUI AgentAPI / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)Supported (Screen coordinate grounding, browser & desktop GUI action loops)
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 toolsNative Web Search Citations + Code Execution Tool + MCP Connectors
Official Fine-Tuning SupportFull Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)Custom Model Tuning via Amazon Bedrock & Prompt Distillation
Multimodal Token BillingText 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 VRAMBF16 / 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 ClassificationOpen-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 ControlSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestext, visiontext, vision
Output Modalitiestexttext

Mistral Medium 3.5 vs Claude Opus 5.5: إجابات سريعة (FAQ)

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

Claude Opus 5.5 is more intelligent. It scores 94 compared with 55 on the composite Intelligence Index.

Which model is faster?

Mistral Medium 3.5 is faster, generating 90 tokens per second compared with 78 tokens per second.

Which model is cheaper to run?

Mistral Medium 3.5 is cheaper at $0.35 per 1M tokens blended, compared with $3.08 (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 1.40s.

Which model has a larger context window?

Claude Opus 5.5 has a larger context window, supporting 1M tokens compared with 262.1K tokens.

الحكم النهائي

Choose Mistral Medium 3.5 for مثالي لـالاستضافة الذاتية على الخوادم الخاصة والضبط الدقيق والسيادة الكاملة على البيانات وأنظمة rag المؤسسية وربط واجهات البرمجة (api) القابلة للتوسع., or choose Claude Opus 5.5 for مثالي لـالاستدلال المؤسسي المتقدم وهندسة البرمجيات وتطبيقات الإنتاج واسعة النطاق وأنظمة rag المؤسسية وربط واجهات البرمجة (api) القابلة للتوسع..

الأسئلة الشائعة (FAQ)

Which is cheaper: Mistral Medium 3.5 or Claude Opus 5.5?+

Mistral Medium 3.5 costs $0.4/1M input and $2/1M output tokens, while Claude Opus 5.5 costs $4/1M input and $20/1M output tokens.

Which model has a larger context window: Mistral Medium 3.5 or Claude Opus 5.5?+

Mistral Medium 3.5 supports 262K tokens whereas Claude Opus 5.5 supports 1M tokens.

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 & PricingContext WindowAI BenchmarksReasoning ModelsTool CallingModel Context Protocol (MCP)

Related reading

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.

المصادر الرسمية: Mistral AI & Anthropic Official Documentation