Head-to-Head Model Comparison

Qwen3 235B-A22B vs Granite 3.3 8B

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.

Qwen3 235B-A22BProfile

Granite 3.3 8BProfile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

Alibaba

Qwen3 235B-A22B

Model Dasar Bobot Terbuka

Qwen3 235B-A22B dari Alibaba adalah model AI yang dirancang untuk self-hosting di server pribadi, fine-tuning, dan kedaulatan data penuh, menghadirkan jendela konteks 131K, kecepatan 68 token/detik, indeks kecerdasan 83/100, serta akses gra

Intelligence Index83 / 100

Input Token:

$0.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

131.1K tokens

SWE-bench Verified:

48.5%

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

Perbedaan Utama Sekilas

Both models cost the same under this workload — choose on capability, not price.
Qwen3 235B-A22B has a larger context window (131K vs 128K tokens).
Granite 3.3 8B is faster at 140 tok/s vs 68 tok/s.

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

Feature	Qwen3 235B-A22B	Granite 3.3 8B
Intelligence Index Composite reasoning & knowledge score (0-100)	83	74
Provider	Alibaba	IBM
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	131.1K tokens~197 A4 pages of text	128K tokens~192 A4 pages of text
Max Output Tokens Per single request	16K	8K
Throughput Speed Tokens generated per second	68 tok/s	140 tok/s
SWE-bench Verified Real-world software engineering	48.5%	N/A
GPQA Diamond Graduate-level reasoning	67%	N/A

Siapa Unggul di Mana?

At-a-glance decision framework

Coding

Evaluations ongoing

Cost

Tied

Identical monthly runtime cost

Speed

Granite 3.3 8B

+106% faster generation

Context

Qwen3 235B-A22B

131.1K tokens window

Skor Benchmark Terverifikasi

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

Qwen3 235B-A22BGranite 3.3 8B

SWE-bench Verified (Autonomous Coding)

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

48.5%vsN/A

GPQA Diamond (Doctorate-Level Science & Math)

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

67%vsN/A

MMLU-Pro (Multi-task Language Understanding)

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

81.5%vs69.5%

LMSYS Chatbot Arena Elo

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

1365ptsvs1235pts

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

68 tok/s vs140 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

Qwen3 235B-A22B0.62s

Granite 3.3 8B0.28s

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

Qwen3 235B-A22B7.97s

Granite 3.3 8B3.85s

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)

Qwen3 235B-A22B Monthly API Bill

$0.00 / month

$0/1M in · $0/1M out

Granite 3.3 8B 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

Qwen3 235B-A22B · Strengths & Key Advantages

Jendela konteks 131K dengan kapasitas output maksimum hingga 16K token (SWE-bench Verified 48.5% · GPQA Diamond 67%)
Kecepatan generasi tinggi 68 token/detik dengan latensi token pertama (TTFT) hanya 620 ms
Bobot terbuka (235B total (22B MoE)) 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

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

Token Use & Task Economics

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

Metric	Qwen3 235B-A22B	Granite 3.3 8B
Cost per Task Estimated USD to finish one task	$0.00	$0.00
Output Tokens / Task Tokens generated per task	22K	12K
Reasoning Tokens / Task Thinking tokens burned per task	8K	2K

Spesifikasi Teknis

Architecture, release timeline, capabilities, and modalities.

Feature	Qwen3 235B-A22B	Granite 3.3 8B
Official API Model ID (SDK)	qwen3-235b-a22b-instruct	granite-3-3-8b
API Protocol	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date	2025-04	2025-04
Knowledge Cutoff	February 2025	January 2025
Architecture	Sparse Mixture-of-Experts Autoregressive Transformer	Enterprise-Calibrated Open Transformer
Parameters	235B total (22B active MoE)	8B
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) · 146 GB VRAM (4-bit Quantized) · 505 GB VRAM (Native BF16)	BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 5 GB VRAM (4-bit Quantized) · 17 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 235B-A22B vs Granite 3.3 8B: Jawaban Cepat (FAQ)

Which is more intelligent, Qwen3 235B-A22B or Granite 3.3 8B?

Qwen3 235B-A22B is more intelligent. It scores 83 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 68 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 0.62s.

Which model has a larger context window?

Qwen3 235B-A22B has a larger context window, supporting 131.1K tokens compared with 128K tokens.

Kesimpulan

Baik Qwen3 235B-A22B (Sangat cocok untuk self-hosting di server pribadi, fine-tuning, dan kedaulatan data penuh, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun 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.) sangat tangguh: Qwen3 235B-A22B unggul dalam penalaran dan pemrograman, Granite 3.3 8B memberikan kecepatan generasi token lebih tinggi, dan Qwen3 235B-A22B lebih hemat biaya untuk penggunaan API skala besar.

Pertanyaan Umum (FAQ)

Mana yang lebih baik untuk coding dan penalaran, Qwen3 235B-A22B atau Granite 3.3 8B?+

Dalam indeks kecerdasan gabungan dan benchmark coding, Qwen3 235B-A22B memimpin. Lihat skor SWE-bench dan GPQA di atas untuk detailnya.

Berapa perbandingan harga API Qwen3 235B-A22B vs Granite 3.3 8B?+

Qwen3 235B-A22B mengenakan biaya $0.00 / $0.00 per 1M token input/output, sedangkan Granite 3.3 8B sebesar $0.00 / $0.00. Secara keseluruhan, Qwen3 235B-A22B lebih hemat biaya.

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

Qwen3 235B-A22B mendukung konteks 131.1K token dibandingkan 128K token pada Granite 3.3 8B, 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)

Qwen3 235B-A22B vs Granite 3.3 8B

Ganti & Bandingkan Model Apa Saja

Qwen3 235B-A22B

Granite 3.3 8B

Siapa Unggul di Mana?

Skor Benchmark Terverifikasi

Latensi & Waktu Respons

Simulator Biaya Token Interaktif

Qwen3 235B-A22B · Strengths & Key Advantages

Considerations & Trade-offs

Granite 3.3 8B · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Spesifikasi Teknis

Qwen3 235B-A22B vs Granite 3.3 8B: Jawaban Cepat (FAQ)

Kesimpulan

Pertanyaan Umum (FAQ)

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