Head-to-Head Model Comparison

Granite 3.3 8B vs Qwen3 32B

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Ditinjau oleh tim riset GetInfoUsPeninjauan terakhir: October 2026Kebijakan editorial

Ganti & Bandingkan Model Apa Saja

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

Granite 3.3 8BProfile

Qwen3 32BProfile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

IBM

Granite 3.3 8B

Model Dasar Bobot Terbuka

Granite 3.3 8B dari IBM adalah model AI yang dirancang untuk self-hosting di server pribadi, fine-tuning, dan kedaulatan data penuh, menghadirkan jendela konteks 128K, kecepatan 140 token/detik, indeks kecerdasan 74/100, serta akses gratis

Intelligence Index74 / 100

Input Token:

$0.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

128K tokens

SWE-bench Verified:

N/A

Alibaba

Qwen3 32B

Model Dasar Bobot Terbuka

Qwen3 32B dari Alibaba adalah model AI yang dirancang untuk self-hosting di server pribadi, fine-tuning, dan kedaulatan data penuh, menghadirkan jendela konteks 131K, kecepatan 85 token/detik, indeks kecerdasan 78/100, serta akses gratis op

Intelligence Index78 / 100

Input Token:

$0.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

131.1K tokens

SWE-bench Verified:

40%

Perbedaan Utama Sekilas

Both models cost the same under this workload — choose on capability, not price.
Qwen3 32B has a larger context window (131K vs 128K tokens).
Granite 3.3 8B is faster at 140 tok/s vs 85 tok/s.

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

Feature	Granite 3.3 8B	Qwen3 32B
Intelligence Index Composite reasoning & knowledge score (0-100)	74	78
Provider	IBM	Alibaba
Input Price Cost per million input tokens	$0.00 / 1M	$0.00 / 1M
Output Price Cost per million output tokens	$0.00 / 1M	$0.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$0.00 / 1M	$0.00 / 1M
Context Window Maximum input + output tokens	128K tokens~192 A4 pages of text	131.1K tokens~197 A4 pages of text
Max Output Tokens Per single request	8K	8K
Throughput Speed Tokens generated per second	140 tok/s	85 tok/s
SWE-bench Verified Real-world software engineering	N/A	40%
GPQA Diamond Graduate-level reasoning	N/A	59%

Siapa Unggul di Mana?

At-a-glance decision framework

Coding

Evaluations ongoing

Cost

Tied

Identical monthly runtime cost

Speed

Granite 3.3 8B

+65% faster generation

Context

Qwen3 32B

131.1K tokens window

Skor Benchmark Terverifikasi

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

Granite 3.3 8BQwen3 32B

SWE-bench Verified (Autonomous Coding)

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

N/Avs40%

GPQA Diamond (Doctorate-Level Science & Math)

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

N/Avs59%

MMLU-Pro (Multi-task Language Understanding)

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

69.5%vs76%

LMSYS Chatbot Arena Elo

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

1235ptsvs1310pts

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

140 tok/s vs85 tok/s

Latensi & Waktu Respons

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

Granite 3.3 8B0.28s

Qwen3 32B0.44s

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

Granite 3.3 8B3.85s

Qwen3 32B6.32s

Simulator Biaya Token Interaktif

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)

Granite 3.3 8B Monthly API Bill

$0.00 / month

$0/1M in · $0/1M out

Qwen3 32B Monthly API Bill

$0.00 / month

$0/1M in · $0/1M out

These models cost the same under this workload — no savings either way.Break-even

Granite 3.3 8B · Strengths & Key Advantages

Jendela konteks 128K dengan kapasitas output maksimum hingga 8K token (MMLU-Pro 69.5% · Arena Elo 1235)
Kecepatan generasi tinggi 140 token/detik dengan latensi token pertama (TTFT) hanya 280 ms
Bobot terbuka (8B) yang siap di-hosting mandiri di GPU lokal atau cloud privat melalui vLLM dan Ollama

Considerations & Trade-offs

Membutuhkan infrastruktur GPU dengan kapasitas VRAM yang memadai untuk eksekusi lokal presisi penuh
Pada tugas pembuktian ilmiah tingkat ekstrem, model penalaran berat kelas atas memberikan kedalaman lebih tinggi

Qwen3 32B · Strengths & Key Advantages

Jendela konteks 131K dengan kapasitas output maksimum hingga 8K token (SWE-bench Verified 40% · GPQA Diamond 59%)
Kecepatan generasi tinggi 85 token/detik dengan latensi token pertama (TTFT) hanya 440 ms
Bobot terbuka (32B) yang siap di-hosting mandiri di GPU lokal atau cloud privat melalui vLLM dan Ollama

Considerations & Trade-offs

Membutuhkan infrastruktur GPU dengan kapasitas VRAM yang memadai untuk eksekusi lokal presisi penuh
Pada tugas pembuktian ilmiah tingkat ekstrem, model penalaran berat kelas atas memberikan kedalaman lebih tinggi

Token Use & Task Economics

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

Metric	Granite 3.3 8B	Qwen3 32B
Cost per Task Estimated USD to finish one task	$0.00	$0.00
Output Tokens / Task Tokens generated per task	12K	16K
Reasoning Tokens / Task Thinking tokens burned per task	2K	4K

Spesifikasi Teknis

Architecture, release timeline, capabilities, and modalities.

Feature	Granite 3.3 8B	Qwen3 32B
Official API Model ID (SDK)	granite-3-3-8b	qwen3-32b-instruct
API Protocol	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date	2025-04	2025-04
Knowledge Cutoff	January 2025	February 2025
Architecture	Enterprise-Calibrated Open Transformer	Dense Autoregressive Transformer
Parameters	8B	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)	Free across full context window (only KV-cache VRAM scales)
Prompt Cache Policy & TTL	Automatic prefix KV-caching in vLLM / SGLang (0 cost)	Automatic prefix KV-caching in vLLM / SGLang (0 cost)
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) · 5 GB VRAM (4-bit Quantized) · 17 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

Granite 3.3 8B vs Qwen3 32B: Jawaban Cepat (FAQ)

Which is more intelligent, Granite 3.3 8B or Qwen3 32B?

Qwen3 32B is more intelligent. It scores 78 compared with 74 on the composite Intelligence Index.

Which model is faster?

Granite 3.3 8B is faster, generating 140 tokens per second compared with 85 tokens per second.

Which model has lower latency?

Granite 3.3 8B has lower latency, with a time to first token of 0.28s compared with 0.44s.

Which model has a larger context window?

Qwen3 32B has a larger context window, supporting 131.1K tokens compared with 128K tokens.

Kesimpulan

Baik Granite 3.3 8B (Sangat cocok untuk self-hosting di server pribadi, fine-tuning, dan kedaulatan data penuh, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun Qwen3 32B (Sangat cocok untuk self-hosting di server pribadi, fine-tuning, dan kedaulatan data penuh, sistem RAG perusahaan, dan integrasi API skala produksi.) sangat tangguh: Qwen3 32B unggul dalam penalaran dan pemrograman, Granite 3.3 8B memberikan kecepatan generasi token lebih tinggi, dan Granite 3.3 8B lebih hemat biaya untuk penggunaan API skala besar.

Pertanyaan Umum (FAQ)

Mana yang lebih baik untuk coding dan penalaran, Granite 3.3 8B atau Qwen3 32B?+

Dalam indeks kecerdasan gabungan dan benchmark coding, Qwen3 32B memimpin. Lihat skor SWE-bench dan GPQA di atas untuk detailnya.

Berapa perbandingan harga API Granite 3.3 8B vs Qwen3 32B?+

Granite 3.3 8B mengenakan biaya $0.00 / $0.00 per 1M token input/output, sedangkan Qwen3 32B sebesar $0.00 / $0.00. Secara keseluruhan, Granite 3.3 8B lebih hemat biaya.

Model mana yang memiliki jendela konteks lebih besar dan kecepatan lebih tinggi?+

Granite 3.3 8B mendukung konteks 128K token dibandingkan 131.1K token pada Qwen3 32B, sementara Granite 3.3 8B unggul dalam kecepatan output token per detik.

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)

Granite 3.3 8B vs Qwen3 32B

Ganti & Bandingkan Model Apa Saja

Granite 3.3 8B

Qwen3 32B

Siapa Unggul di Mana?

Skor Benchmark Terverifikasi

Latensi & Waktu Respons

Simulator Biaya Token Interaktif

Granite 3.3 8B · Strengths & Key Advantages

Considerations & Trade-offs

Qwen3 32B · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Spesifikasi Teknis

Granite 3.3 8B vs Qwen3 32B: Jawaban Cepat (FAQ)

Kesimpulan

Pertanyaan Umum (FAQ)

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