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Head-to-Head Model Comparison

o3-pro vs Qwen3.8 Max Preview

Benchmarks, API Token Pricing, Context Window & Speed Comparison

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

Compare o3-pro by OpenAI against Qwen3.8 Max Preview by Alibaba across real-world coding, reasoning, token economics, and latency.

مقارنة مباشرة (VS)

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OpenAI

o3-pro

محرك استدلال منطقي عميق

نموذج o3-pro من OpenAI مصمم خصيصاً لـالاستدلال المنطقي العميق والرياضيات المتقدمة والبحث العلمي متعدد الخطوات، حيث يوفر نافذة سياق بسعة 200K وسرعة 30 رمز/ثانية ومؤشر ذكاء 58/100 (بتكلفة $20/$80 لكل مليون رمز).

Intelligence Index58 / 100
Input Token:

$20.00 / 1M

Output Token:

$80.00 / 1M

Context Window:

200K tokens

SWE-bench Verified:

71.5%

Alibaba

Qwen3.8 Max Preview

نموذج أساسي مفتوح الأوزان

نموذج Qwen3.8 Max Preview من Alibaba مصمم خصيصاً لـالاستضافة الذاتية على الخوادم الخاصة والضبط الدقيق والسيادة الكاملة على البيانات، حيث يوفر نافذة سياق بسعة 1M وسرعة 60 رمز/ثانية ومؤشر ذكاء 93/100 (وصول مجاني بأوزان مفتوحة).

Intelligence Index93 / 100
Input Token:

$0.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

75.2%

أهم الفروقات في لمحة

  • Qwen3.8 Max Preview is 1.0x cheaper for API usage (input + output tokens combined).
  • Qwen3.8 Max Preview has a larger context window (1M vs 200K tokens).
  • Qwen3.8 Max Preview is faster at 60 tok/s vs 30 tok/s.
  • Qwen3.8 Max Preview leads on SWE-bench coding (75.2% vs 71.5%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
Featureo3-proQwen3.8 Max Preview
Intelligence Index
Composite reasoning & knowledge score (0-100)
5893
Provider
OpenAIAlibaba
Input Price
Cost per million input tokens
$20.00 / 1M$0.00 / 1M
Output Price
Cost per million output tokens
$80.00 / 1M$0.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$15.50 / 1M$0.00 / 1M
Context Window
Maximum input + output tokens
200K tokens~300 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
100K32K
Throughput Speed
Tokens generated per second
30 tok/s60 tok/s
SWE-bench Verified
Real-world software engineering
71.5%75.2%
GPQA Diamond
Graduate-level reasoning
79.5%79.5%
Cached Input Price
Prompt caching discount per 1M tokens
$5.00 / 1M$0.00 / 1M

من يتفوق في كل مجال؟

At-a-glance decision framework
Coding
Qwen3.8 Max Preview
+3.7% SWE-bench lead
Cost
Qwen3.8 Max Preview
1.0x cheaper monthly runtime
Speed
Qwen3.8 Max Preview
+100% faster generation
Context
Qwen3.8 Max Preview
1M tokens window

نتائج الاختبارات المعيارية الموثقة

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

o3-proQwen3.8 Max Preview
SWE-bench Verified (Autonomous Coding)

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

71.5%vs75.2%
GPQA Diamond (Doctorate-Level Science & Math)

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

79.5%vs79.5%
MMLU-Pro (Multi-task Language Understanding)

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

88.5%vs89%
LMSYS Chatbot Arena Elo

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

1352ptsvs1485pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

13.6%vsN/A
Terminal-Bench (Agentic Coding & Terminal Use)

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

47.5%vsN/A
SciCode (Scientific Computing)

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

45.5%vsN/A
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

73%vs77%
AIME (Advanced Math Competition)

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

93%vsN/A
Long-Context Reasoning

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

80.5%vsN/A
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

30 tok/s vs60 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
o3-pro5.20s
Qwen3.8 Max Preview0.68s
Est. End-to-End Response (500 tokens)TTFT + generation time
o3-pro21.87s
Qwen3.8 Max Preview9.01s

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)
o3-pro Monthly API Bill
$109.50 / month
$20/1M in · $80/1M out
Qwen3.8 Max Preview Monthly API Bill
$0.00 / month
$0/1M in · $0/1M out
Qwen3.8 Max Preview saves approximately $109.50 / month (100%) under this workload.1.0x Savings

o3-pro · Strengths & Key Advantages

  • نافذة سياق بسعة 200K وحد أقصى للمخرجات يصل إلى 100K رمز (SWE-bench Verified 71.5% · GPQA Diamond 79.5%)
  • سرعة توليد عالية تبلغ 30 رمز/ثانية مع زمن استجابة لأول رمز (TTFT) قدره 5200 مللي ثانية
  • تسعير API تنافسي (بتكلفة $20/$80 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

Qwen3.8 Max Preview · Strengths & Key Advantages

  • نافذة سياق بسعة 1M وحد أقصى للمخرجات يصل إلى 32K رمز (SWE-bench Verified 75.2% · GPQA Diamond 79.5%)
  • سرعة توليد عالية تبلغ 60 رمز/ثانية مع زمن استجابة لأول رمز (TTFT) قدره 680 مللي ثانية
  • أوزان مفتوحة (2.4T total (95B 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

Token Use & Task Economics

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

Metrico3-proQwen3.8 Max Preview
Cost per Task
Estimated USD to finish one task
$11.68$0.00
Output Tokens / Task
Tokens generated per task
58K35K
Reasoning Tokens / Task
Thinking tokens burned per task
38K15K

المواصفات التقنية

Architecture, release timeline, capabilities, and modalities.

Featureo3-proQwen3.8 Max Preview
Official API Model ID (SDK)o3-proqwen3-8-max-preview-instruct
API ProtocolOpenAI Responses API & Chat Completions v1OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date2025-062026-07
Knowledge CutoffJune 2024April 2026
ArchitectureHigh-effort reasoning transformerColossus-Scale Open Sparse Mixture-of-Experts
ParametersConfidential2.4T total (95B active MoE)
Enterprise Rate Limits (RPM / TPM)10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPMUnlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud
Long-Context Tier (>128K/200K)Flat rate ($20/1M in) across full 200K windowFree across full context window (only KV-cache VRAM scales)
Prompt Cache Policy & TTLAutomatic prefix caching at $5/1M (no extra cache-write fee)Automatic prefix KV-caching in vLLM / SGLang (0 cost)
Computer Use / GUI AgentSupported (Screen coordinate grounding, browser & desktop GUI action loops)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 & SandboxNative Web Search tool + Hosted Code Interpreter & File Search RAGSupported via external Tavily/Exa Search & E2B/Docker Sandbox tools
Official Fine-Tuning SupportSupervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)
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 VRAMCloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 1488 GB VRAM (4-bit Quantized) · 5160 GB VRAM (Native BF16)
Safety & Frontier ClassificationOpenAI Preparedness Framework Audited & System Card PublishedOpen-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)
Enterprise Compliance (ZDR/HIPAA/SOC2)SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control
Input Modalitiestext, visiontext, vision
Output Modalitiestexttext

o3-pro vs Qwen3.8 Max Preview: إجابات سريعة (FAQ)

Which is more intelligent, o3-pro or Qwen3.8 Max Preview?

Qwen3.8 Max Preview is more intelligent. It scores 93 compared with 58 on the composite Intelligence Index.

Which model is faster?

Qwen3.8 Max Preview is faster, generating 60 tokens per second compared with 30 tokens per second.

Which model is cheaper to run?

Qwen3.8 Max Preview is cheaper at $0.00 per 1M tokens blended, compared with $15.50 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Qwen3.8 Max Preview has lower latency, with a time to first token of 0.68s compared with 5.20s.

Which model has a larger context window?

Qwen3.8 Max Preview has a larger context window, supporting 1M tokens compared with 200K tokens.

الحكم النهائي

Choose o3-pro for مثالي لـالاستدلال المنطقي العميق والرياضيات المتقدمة والبحث العلمي متعدد الخطوات وأنظمة rag المؤسسية وربط واجهات البرمجة (api) القابلة للتوسع., or choose Qwen3.8 Max Preview for مثالي لـالاستضافة الذاتية على الخوادم الخاصة والضبط الدقيق والسيادة الكاملة على البيانات وأنظمة rag المؤسسية وربط واجهات البرمجة (api) القابلة للتوسع..

الأسئلة الشائعة (FAQ)

Which is cheaper: o3-pro or Qwen3.8 Max Preview?+

o3-pro costs $20/1M input and $80/1M output tokens, while Qwen3.8 Max Preview costs $0/1M input and $0/1M output tokens.

Which model has a larger context window: o3-pro or Qwen3.8 Max Preview?+

o3-pro supports 200K tokens whereas Qwen3.8 Max Preview 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: OpenAI & Alibaba Official Documentation