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Head-to-Head Model Comparison

Qwen3 235B-A22B vs QwQ 32B Preview

Benchmarks, API Token Pricing, Context Window & Speed Comparison

GetInfoUs araştırma ekibi tarafından incelendiSon inceleme: October 2026Yayın ilkeleri
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Qwen3 235B-A22B vs QwQ 32B Preview: Benchmarks, Pricing & Speed Comparison

Alibaba tarafından geliştirilen Qwen3 235B-A22B ve Alibaba tarafından sunulan QwQ 32B Preview, kendi sınıflarının öne çıkan yapay zeka modelleridir. Qwen3 235B-A22B, 131.1K token bağlam penceresi ve 1M token başına $0.00/$0.00 fiyat sunarken; QwQ 32B Preview, 32.8K token bağlam penceresi ve $0.20/$0.60 fiyatla gelir. Aşağıda tüm benchmark, hız ve maliyet detaylarını inceleyebilirsiniz.

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Alibaba

Qwen3 235B-A22B

Açık Ağırlıklı Temel Model

Alibaba tarafından geliştirilen Qwen3 235B-A22B; özel sunucuda kendi kendine barındırma (self-hosting), ince ayar ve tam veri egemenliği için tasarlanmış olup 131K bağlam penceresi, 68 token/sn hız, 83/100 zeka indeksi ve ücretsiz açık ağır

Intelligence Index83 / 100
Input Token:

$0.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

131.1K tokens

SWE-bench Verified:

48.5%

Alibaba

QwQ 32B Preview

Açık Ağırlıklı Akıl Yürütme

Alibaba tarafından geliştirilen QwQ 32B Preview; yüksek verimli açık ağırlıklı düşünce zinciri (Chain-of-Thought) akıl yürütme için tasarlanmış olup 33K bağlam penceresi, 52 token/sn hız, 47/100 zeka indeksi ve 1M token başına $0.2/$0.6 fiy

Intelligence Index47 / 100
Input Token:

$0.20 / 1M

Output Token:

$0.60 / 1M

Context Window:

32.8K tokens

SWE-bench Verified:

54.2%

Bir Bakışta Temel Farklar

  • Qwen3 235B-A22B is 1.0x cheaper for API usage (input + output tokens combined).
  • Qwen3 235B-A22B has a larger context window (131K vs 33K tokens).
  • Qwen3 235B-A22B is faster at 68 tok/s vs 52 tok/s.
  • QwQ 32B Preview leads on SWE-bench coding (54.2% vs 48.5%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureQwen3 235B-A22BQwQ 32B Preview
Intelligence Index
Composite reasoning & knowledge score (0-100)
8347
Provider
AlibabaAlibaba
Input Price
Cost per million input tokens
$0.00 / 1M$0.20 / 1M
Output Price
Cost per million output tokens
$0.00 / 1M$0.60 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.00 / 1M$0.14 / 1M
Context Window
Maximum input + output tokens
131.1K tokens~197 A4 pages of text32.8K tokens~49 A4 pages of text
Max Output Tokens
Per single request
16K8K
Throughput Speed
Tokens generated per second
68 tok/s52 tok/s
SWE-bench Verified
Real-world software engineering
48.5%54.2%
GPQA Diamond
Graduate-level reasoning
67%65.2%
Cached Input Price
Prompt caching discount per 1M tokens
$0.00 / 1M$0.05 / 1M

Hangi Alanda Kim Kazanıyor?

At-a-glance decision framework
Coding
QwQ 32B Preview
+5.7% SWE-bench lead
Cost
Qwen3 235B-A22B
1.0x cheaper monthly runtime
Speed
Qwen3 235B-A22B
+31% faster generation
Context
Qwen3 235B-A22B
131.1K tokens window

Doğrulanmış Benchmark Puanları

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

Qwen3 235B-A22BQwQ 32B Preview
SWE-bench Verified (Autonomous Coding)

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

48.5%vs54.2%
GPQA Diamond (Doctorate-Level Science & Math)

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

67%vs65.2%
MMLU-Pro (Multi-task Language Understanding)

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

81.5%vs74.8%
LMSYS Chatbot Arena Elo

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

1365ptsvs1312pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

N/Avs9.8%
Terminal-Bench (Agentic Coding & Terminal Use)

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

N/Avs29.5%
SciCode (Scientific Computing)

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

N/Avs36.2%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs58.4%
AIME (Advanced Math Competition)

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

N/Avs79.7%
Long-Context Reasoning

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

N/Avs60.1%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

68 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
Qwen3 235B-A22B0.62s
QwQ 32B Preview0.82s
Est. End-to-End Response (500 tokens)TTFT + generation time
Qwen3 235B-A22B7.97s
QwQ 32B Preview10.44s

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)
Qwen3 235B-A22B Monthly API Bill
$0.00 / month
$0/1M in · $0/1M out
QwQ 32B Preview Monthly API Bill
$0.92 / month
$0.2/1M in · $0.6/1M out
Qwen3 235B-A22B saves approximately $0.92 / month (100%) under this workload.1.0x Savings

Qwen3 235B-A22B · Strengths & Key Advantages

  • 131K bağlam penceresi ve yanıt başına maksimum 16K çıktı tokenı kapasitesi (SWE-bench Verified 48.5% · GPQA Diamond 67%)
  • Sadece 620 ms ilk token gecikmesi (TTFT) ile saniyede 68 token yüksek üretim hızı
  • vLLM, SGLang veya Ollama üzerinden yerel GPU sunucularında barındırılabilen açık ağırlıklı mimari (235B total (22B 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

QwQ 32B Preview · Strengths & Key Advantages

  • 33K bağlam penceresi ve yanıt başına maksimum 8K çıktı tokenı kapasitesi (SWE-bench Verified 54.2% · GPQA Diamond 65.2%)
  • Sadece 820 ms ilk token gecikmesi (TTFT) ile saniyede 52 token yüksek üretim hızı
  • vLLM, SGLang veya Ollama üzerinden yerel GPU sunucularında barındırılabilen açık ağırlıklı mimari (32B)
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.

MetricQwen3 235B-A22BQwQ 32B Preview
Cost per Task
Estimated USD to finish one task
$0.00$0.45
Output Tokens / Task
Tokens generated per task
22K22K
Reasoning Tokens / Task
Thinking tokens burned per task
8K18K

Teknik Özellikler

Architecture, release timeline, capabilities, and modalities.

FeatureQwen3 235B-A22BQwQ 32B Preview
Official API Model ID (SDK)qwen3-235b-a22b-instructqwq-32b-instruct
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date2025-042024-11
Knowledge CutoffFebruary 2025September 2024
ArchitectureSparse Mixture-of-Experts Autoregressive TransformerReinforcement Learning Reasoning Transformer
Parameters235B total (22B active MoE)32B
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)Free across full context window (only KV-cache VRAM scales)Flat rate ($0.2/1M in) across full 33K window
Prompt Cache Policy & TTLAutomatic prefix KV-caching in vLLM / SGLang (0 cost)Cached input at $0.05/1M tokens
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
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) · 146 GB VRAM (4-bit Quantized) · 505 GB VRAM (Native BF16)BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 20 GB VRAM (4-bit Quantized) · 69 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

Qwen3 235B-A22B vs QwQ 32B Preview: Hızlı Yanıtlar (SSS)

Which is more intelligent, Qwen3 235B-A22B or QwQ 32B Preview?

Qwen3 235B-A22B is more intelligent. It scores 83 compared with 47 on the composite Intelligence Index.

Which model is faster?

Qwen3 235B-A22B is faster, generating 68 tokens per second compared with 52 tokens per second.

Which model is cheaper to run?

Qwen3 235B-A22B is cheaper at $0.00 per 1M tokens blended, compared with $0.14 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Qwen3 235B-A22B has lower latency, with a time to first token of 0.62s compared with 0.82s.

Which model has a larger context window?

Qwen3 235B-A22B has a larger context window, supporting 131.1K tokens compared with 32.8K tokens.

Sonuç

Hem Qwen3 235B-A22B (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 QwQ 32B Preview (yüksek verimli açık ağırlıklı düşünce zinciri (Chain-of-Thought) akıl yürütme, kurumsal RAG mimarileri ve ölçeklenebilir üretim API entegrasyonları için idealdir.) güçlü üretim seçenekleridir: Qwen3 235B-A22B karmaşık akıl yürütme ve kodlama testlerinde öne çıkarken, Qwen3 235B-A22B daha yüksek üretim hızı sağlar; Qwen3 235B-A22B ise yüksek hacimli API kullanımlarında daha ekonomiktir.

Sıkça Sorulan Sorular (SSS)

Kodlama ve akıl yürütme için Qwen3 235B-A22B mi yoksa QwQ 32B Preview mi daha iyi?+

Bileşik zeka endeksi ve yazılım testlerinde Qwen3 235B-A22B önde yer alıyor. Detaylı karşılaştırma için yukarıdaki SWE-bench ve GPQA tablolarına göz atabilirsiniz.

Qwen3 235B-A22B ve QwQ 32B Preview API fiyatları nasıl karşılaştırılır?+

Qwen3 235B-A22B 1M giriş/çıkış tokeni başına $0.00 / $0.00 ücretlendirilirken, QwQ 32B Preview $0.20 / $0.60 seviyesindedir. Karma maliyette Qwen3 235B-A22B daha avantajlıdır.

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

Qwen3 235B-A22B 131.1K token bağlam penceresi sunarken QwQ 32B Preview 32.8K token kapasiteye sahiptir. Saniyedeki token üretim hızında ise Qwen3 235B-A22B 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 & 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.

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