Head-to-Head Model Comparison

Qwen3-Coder 30B-A3B Instruct vs Qwen 2.5 Coder 32B

Benchmarks, API Token Pricing, Context Window & Speed Comparison

GetInfoUs araştırma ekibi tarafından incelendiSon inceleme: October 2026Yayın ilkeleri

Paylaş

İstediğiniz Modelleri Seçin ve Karşılaştırın

Select any AI models from our verified benchmark database to generate live side-by-side matrices.

Qwen3-Coder 30B-A3B InstructProfile

Qwen 2.5 Coder 32BProfile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

Alibaba

Qwen3-Coder 30B-A3B Instruct

Açık Ağırlıklı Temel Model

Alibaba tarafından geliştirilen Qwen3-Coder 30B-A3B Instruct; özel sunucuda kendi kendine barındırma (self-hosting), ince ayar ve tam veri egemenliği için tasarlanmış olup 262K bağlam penceresi, 140 token/sn hız, 76/100 zeka indeksi ve ücre

Intelligence Index76 / 100

Input Token:

$0.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

262.1K tokens

SWE-bench Verified:

N/A

Alibaba

Qwen 2.5 Coder 32B

Açık Ağırlıklı Kodlama Uzmanı

Alibaba tarafından geliştirilen Qwen 2.5 Coder 32B; kendi sunucunuzda barındırılabilir açık ağırlıklı yazılım geliştirme ve kod üretimi için tasarlanmış olup 128K bağlam penceresi, 78 token/sn hız, 43/100 zeka indeksi ve 1M token başına $0.

Intelligence Index43 / 100

Input Token:

$0.20 / 1M

Output Token:

$0.60 / 1M

Context Window:

128K tokens

SWE-bench Verified:

48.6%

Bir Bakışta Temel Farklar

Qwen3-Coder 30B-A3B Instruct is 1.0x cheaper for API usage (input + output tokens combined).
Qwen3-Coder 30B-A3B Instruct has a larger context window (262K vs 128K tokens).
Qwen3-Coder 30B-A3B Instruct is faster at 140 tok/s vs 78 tok/s.

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

Feature	Qwen3-Coder 30B-A3B Instruct	Qwen 2.5 Coder 32B
Intelligence Index Composite reasoning & knowledge score (0-100)	76	43
Provider	Alibaba	Alibaba
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	$0.13 / 1M
Context Window Maximum input + output tokens	262.1K tokens~393 A4 pages of text	128K tokens~192 A4 pages of text
Max Output Tokens Per single request	8K	8K
Throughput Speed Tokens generated per second	140 tok/s	78 tok/s
SWE-bench Verified Real-world software engineering	N/A	48.6%
GPQA Diamond Graduate-level reasoning	N/A	48.2%
Cached Input Price Prompt caching discount per 1M tokens	$0.00 / 1M	$0.04 / 1M

Hangi Alanda Kim Kazanıyor?

At-a-glance decision framework

Coding

Evaluations ongoing

Cost

Qwen3-Coder 30B-A3B Instruct

1.0x cheaper monthly runtime

Speed

Qwen3-Coder 30B-A3B Instruct

+79% faster generation

Context

Qwen3-Coder 30B-A3B Instruct

262.1K tokens window

Doğrulanmış Benchmark Puanları

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

Qwen3-Coder 30B-A3B InstructQwen 2.5 Coder 32B

SWE-bench Verified (Autonomous Coding)

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

N/Avs48.6%

GPQA Diamond (Doctorate-Level Science & Math)

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

N/Avs48.2%

MMLU-Pro (Multi-task Language Understanding)

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

74%vs68.9%

LMSYS Chatbot Arena Elo

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

1285ptsvs1268pts

Humanity's Last Exam (Frontier Expert Knowledge)

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

N/Avs6.8%

Terminal-Bench (Agentic Coding & Terminal Use)

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

N/Avs32.4%

SciCode (Scientific Computing)

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

N/Avs31.8%

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

63%vs53.2%

AIME (Advanced Math Competition)

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

N/Avs55.4%

Long-Context Reasoning

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

N/Avs65.4%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

140 tok/s vs78 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-Coder 30B-A3B Instruct0.28s

Qwen 2.5 Coder 32B0.54s

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

Qwen3-Coder 30B-A3B Instruct3.85s

Qwen 2.5 Coder 32B6.95s

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)

Qwen3-Coder 30B-A3B Instruct Monthly API Bill

$0.00 / month

$0/1M in · $0/1M out

Qwen 2.5 Coder 32B Monthly API Bill

$0.90 / month

$0.2/1M in · $0.6/1M out

Qwen3-Coder 30B-A3B Instruct saves approximately $0.90 / month (100%) under this workload.1.0x Savings

Qwen3-Coder 30B-A3B Instruct · Strengths & Key Advantages

262K bağlam penceresi ve yanıt başına maksimum 8K çıktı tokenı kapasitesi (MMLU-Pro 74% · Arena Elo 1285)
Sadece 280 ms ilk token gecikmesi (TTFT) ile saniyede 140 token yüksek üretim hızı
vLLM, SGLang veya Ollama üzerinden yerel GPU sunucularında barındırılabilen açık ağırlıklı mimari (30B total (3B 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

Qwen 2.5 Coder 32B · Strengths & Key Advantages

128K bağlam penceresi ve yanıt başına maksimum 8K çıktı tokenı kapasitesi (SWE-bench Verified 48.6% · GPQA Diamond 48.2%)
Sadece 540 ms ilk token gecikmesi (TTFT) ile saniyede 78 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.

Metric	Qwen3-Coder 30B-A3B Instruct	Qwen 2.5 Coder 32B
Cost per Task Estimated USD to finish one task	$0.00	$0.18
Output Tokens / Task Tokens generated per task	15K	35K
Reasoning Tokens / Task Thinking tokens burned per task	0K	0K

Teknik Özellikler

Architecture, release timeline, capabilities, and modalities.

Feature	Qwen3-Coder 30B-A3B Instruct	Qwen 2.5 Coder 32B
Official API Model ID (SDK)	qwen3-coder-30b-a3b-instruct	qwen-2-5-coder-32b-instruct
API Protocol	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date	2025-04	2024-11
Knowledge Cutoff	March 2025	September 2024
Architecture	Compact Sparse Mixture-of-Experts Transformer	Dense Code-Specialized Transformer
Parameters	30B total (3B 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 Cloud	Unlimited (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 128K window
Prompt Cache Policy & TTL	Automatic prefix KV-caching in vLLM / SGLang (0 cost)	Cached input at $0.04/1M tokens
Computer Use / GUI Agent	API / 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 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	Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools
Official Fine-Tuning Support	Full 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 Billing	Text BPE (~4 chars/token)	Text BPE (~4 chars/token)
Quantization & Min GPU VRAM	BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 19 GB VRAM (4-bit Quantized) · 65 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 Classification	Open-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 Control	100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control
Input Modalities	text	text
Output Modalities	text	text

Qwen3-Coder 30B-A3B Instruct vs Qwen 2.5 Coder 32B: Hızlı Yanıtlar (SSS)

Which is more intelligent, Qwen3-Coder 30B-A3B Instruct or Qwen 2.5 Coder 32B?

Qwen3-Coder 30B-A3B Instruct is more intelligent. It scores 76 compared with 43 on the composite Intelligence Index.

Which model is faster?

Qwen3-Coder 30B-A3B Instruct is faster, generating 140 tokens per second compared with 78 tokens per second.

Which model is cheaper to run?

Qwen3-Coder 30B-A3B Instruct is cheaper at $0.00 per 1M tokens blended, compared with $0.13 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Qwen3-Coder 30B-A3B Instruct has lower latency, with a time to first token of 0.28s compared with 0.54s.

Which model has a larger context window?

Qwen3-Coder 30B-A3B Instruct has a larger context window, supporting 262.1K tokens compared with 128K tokens.

Sonuç

Hem Qwen3-Coder 30B-A3B Instruct (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 Qwen 2.5 Coder 32B (kendi sunucunuzda barındırılabilir açık ağırlıklı yazılım geliştirme ve kod üretimi, kurumsal RAG mimarileri ve ölçeklenebilir üretim API entegrasyonları için idealdir.) güçlü üretim seçenekleridir: Qwen3-Coder 30B-A3B Instruct karmaşık akıl yürütme ve kodlama testlerinde öne çıkarken, Qwen3-Coder 30B-A3B Instruct daha yüksek üretim hızı sağlar; Qwen3-Coder 30B-A3B Instruct ise yüksek hacimli API kullanımlarında daha ekonomiktir.

Sıkça Sorulan Sorular (SSS)

Kodlama ve akıl yürütme için Qwen3-Coder 30B-A3B Instruct mi yoksa Qwen 2.5 Coder 32B mi daha iyi?+

Bileşik zeka endeksi ve yazılım testlerinde Qwen3-Coder 30B-A3B Instruct önde yer alıyor. Detaylı karşılaştırma için yukarıdaki SWE-bench ve GPQA tablolarına göz atabilirsiniz.

Qwen3-Coder 30B-A3B Instruct ve Qwen 2.5 Coder 32B API fiyatları nasıl karşılaştırılır?+

Qwen3-Coder 30B-A3B Instruct 1M giriş/çıkış tokeni başına $0.00 / $0.00 ücretlendirilirken, Qwen 2.5 Coder 32B $0.20 / $0.60 seviyesindedir. Karma maliyette Qwen3-Coder 30B-A3B Instruct daha avantajlıdır.

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

Qwen3-Coder 30B-A3B Instruct 262.1K token bağlam penceresi sunarken Qwen 2.5 Coder 32B 128K token kapasiteye sahiptir. Saniyedeki token üretim hızında ise Qwen3-Coder 30B-A3B Instruct 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)

Qwen3-Coder 30B-A3B Instruct vs Qwen 2.5 Coder 32B

İstediğiniz Modelleri Seçin ve Karşılaştırın

Qwen3-Coder 30B-A3B Instruct

Qwen 2.5 Coder 32B

Hangi Alanda Kim Kazanıyor?

Doğrulanmış Benchmark Puanları

Gecikme Süresi ve Yanıt Hızı

Gerçek Zamanlı Token Maliyet Simülatörü

Qwen3-Coder 30B-A3B Instruct · Strengths & Key Advantages

Considerations & Trade-offs

Qwen 2.5 Coder 32B · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Teknik Özellikler

Qwen3-Coder 30B-A3B Instruct vs Qwen 2.5 Coder 32B: Hızlı Yanıtlar (SSS)

Sonuç

Sıkça Sorulan Sorular (SSS)

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