Head-to-Head Model Comparison

Gemini 2.5 Computer Use vs Gemini 2.5 Flash

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Ditinjau oleh tim riset GetInfoUsPeninjauan terakhir: October 2026Kebijakan editorial

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

Gemini 2.5 Computer UseProfile

Gemini 2.5 FlashProfile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

Google

Gemini 2.5 Computer Use

Model Agen Otonom & Alat

Gemini 2.5 Computer Use dari Google adalah model AI yang dirancang untuk alur kerja agen otonom, pemanggilan alat (tool calling), dan otomatisasi multi-langkah, menghadirkan jendela konteks 128K, kecepatan 85 token/detik, indeks kecerdasan

Intelligence Index65 / 100

Input Token:

$1.50 / 1M

Output Token:

$8.00 / 1M

Context Window:

128K tokens

SWE-bench Verified:

N/A

Google

Gemini 2.5 Flash

Inferensi Super Cepat

Gemini 2.5 Flash dari Google adalah model AI yang dirancang untuk interaksi real-time dengan latensi sangat rendah dan routing bervolume tinggi, menghadirkan jendela konteks 1.0M, kecepatan 160 token/detik, indeks kecerdasan 68/100, serta t

Intelligence Index68 / 100

Input Token:

$0.30 / 1M

Output Token:

$2.50 / 1M

Context Window:

1.05M tokens

SWE-bench Verified:

58.2%

Perbedaan Utama Sekilas

Gemini 2.5 Flash is 3.6x cheaper for API usage (input + output tokens combined).
Gemini 2.5 Flash has a larger context window (1M vs 128K tokens).
Gemini 2.5 Flash is faster at 160 tok/s vs 85 tok/s.

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

Feature	Gemini 2.5 Computer Use	Gemini 2.5 Flash
Intelligence Index Composite reasoning & knowledge score (0-100)	65	68
Provider	Google	Google
Input Price Cost per million input tokens	$1.50 / 1M	$0.30 / 1M
Output Price Cost per million output tokens	$8.00 / 1M	$2.50 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$1.36 / 1M	$0.36 / 1M
Context Window Maximum input + output tokens	128K tokens~192 A4 pages of text	1.05M tokens~1,573 A4 pages of text
Max Output Tokens Per single request	16K	66K
Throughput Speed Tokens generated per second	85 tok/s	160 tok/s
SWE-bench Verified Real-world software engineering	N/A	58.2%
GPQA Diamond Graduate-level reasoning	N/A	75.4%
Cached Input Price Prompt caching discount per 1M tokens	$0.38 / 1M	$0.07 / 1M

Siapa Unggul di Mana?

At-a-glance decision framework

Coding

Evaluations ongoing

Cost

Gemini 2.5 Flash

3.6x cheaper monthly runtime

Speed

Gemini 2.5 Flash

+88% faster generation

Context

Gemini 2.5 Flash

1.05M tokens window

Skor Benchmark Terverifikasi

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

Gemini 2.5 Computer UseGemini 2.5 Flash

SWE-bench Verified (Autonomous Coding)

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

N/Avs58.2%

GPQA Diamond (Doctorate-Level Science & Math)

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

N/Avs75.4%

MMLU-Pro (Multi-task Language Understanding)

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

N/Avs83.2%

LMSYS Chatbot Arena Elo

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

1365ptsvs1385pts

Terminal-Bench (Agentic Coding & Terminal Use)

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

45.2%vsN/A

AIME (Advanced Math Competition)

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

N/Avs84.5%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

85 tok/s vs160 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

Gemini 2.5 Computer Use0.65s

Gemini 2.5 Flash0.45s

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

Gemini 2.5 Computer Use6.53s

Gemini 2.5 Flash3.58s

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)

Gemini 2.5 Computer Use Monthly API Bill

$10.01 / month

$1.5/1M in · $8/1M out

Gemini 2.5 Flash Monthly API Bill

$2.81 / month

$0.3/1M in · $2.5/1M out

Gemini 2.5 Flash saves approximately $7.20 / month (72%) under this workload.3.6x Savings

Gemini 2.5 Computer Use · Strengths & Key Advantages

Jendela konteks 128K dengan kapasitas output maksimum hingga 16K token (Arena Elo 1365)
Kecepatan generasi tinggi 85 token/detik dengan latensi token pertama (TTFT) hanya 650 ms
Skema harga API kompetitif (tarif $1.5/$8 per 1M token) dengan dukungan cache prompt dan output JSON terstruktur

Considerations & Trade-offs

Model cloud proprietari tertutup; bobot model tidak dapat diunduh untuk penggunaan lokal offline
Pada tugas pembuktian ilmiah tingkat ekstrem, model penalaran berat kelas atas memberikan kedalaman lebih tinggi

Gemini 2.5 Flash · Strengths & Key Advantages

Jendela konteks 1.0M dengan kapasitas output maksimum hingga 66K token (SWE-bench Verified 58.2% · GPQA Diamond 75.4%)
Kecepatan generasi tinggi 160 token/detik dengan latensi token pertama (TTFT) hanya 450 ms
Skema harga API kompetitif (tarif $0.3/$2.5 per 1M token) dengan dukungan cache prompt dan output JSON terstruktur

Considerations & Trade-offs

Model cloud proprietari tertutup; bobot model tidak dapat diunduh untuk penggunaan lokal offline
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	Gemini 2.5 Computer Use	Gemini 2.5 Flash
Cost per Task Estimated USD to finish one task	$1.15	$0.85
Output Tokens / Task Tokens generated per task	15K	32K
Reasoning Tokens / Task Thinking tokens burned per task	6K	14K

Spesifikasi Teknis

Architecture, release timeline, capabilities, and modalities.

Feature	Gemini 2.5 Computer Use	Gemini 2.5 Flash
Official API Model ID (SDK)	models/gemini-2-5-computer-use	models/gemini-2-5-flash
API Protocol	Google Gemini API (generateContent) + OpenAI-Compatible SDK	Google Gemini API (generateContent) + OpenAI-Compatible SDK
Release Date	2025-10	2025-06
Knowledge Cutoff	June 2025	March 2025
Architecture	Action-grounded vision-language agent model	High-throughput sparse multimodal transformer with thinking mode
Parameters	Confidential	Confidential
Enterprise Rate Limits (RPM / TPM)	10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM	10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)	Flat rate ($1.5/1M in) across full 128K window	Standard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTL	Implicit + Explicit Context Caching at $0.375/1M with configurable TTL	Implicit + Explicit Context Caching at $0.075/1M with configurable TTL
Computer Use / GUI Agent	Supported (Screen coordinate grounding, browser & desktop GUI action loops)	Supported (Screen coordinate grounding, browser & desktop GUI action loops)
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	Built-in Google Search Grounding + Managed Python Code Execution Sandbox	Built-in Google Search Grounding + Managed Python Code Execution Sandbox
Official Fine-Tuning Support	Vertex AI Supervised Adapter Tuning & Context Distillation	Vertex AI Supervised Adapter Tuning & Context Distillation
Multimodal Token Billing	Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)	Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec) · Video (~258–300 tokens/sec)
Quantization & Min GPU VRAM	Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)	Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)
Safety & Frontier Classification	Google DeepMind Frontier Safety Framework Verified	Google DeepMind Frontier Safety Framework Verified
Enterprise Compliance (ZDR/HIPAA/SOC2)	SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier	SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalities	text, vision	text, vision, audio, video
Output Modalities	text	text

Gemini 2.5 Computer Use vs Gemini 2.5 Flash: Jawaban Cepat (FAQ)

Which is more intelligent, Gemini 2.5 Computer Use or Gemini 2.5 Flash?

Gemini 2.5 Flash is more intelligent. It scores 68 compared with 65 on the composite Intelligence Index.

Which model is faster?

Gemini 2.5 Flash is faster, generating 160 tokens per second compared with 85 tokens per second.

Which model is cheaper to run?

Gemini 2.5 Flash is cheaper at $0.36 per 1M tokens blended, compared with $1.36 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Gemini 2.5 Flash has lower latency, with a time to first token of 0.45s compared with 0.65s.

Which model has a larger context window?

Gemini 2.5 Flash has a larger context window, supporting 1.05M tokens compared with 128K tokens.

Kesimpulan

Baik Gemini 2.5 Computer Use (Sangat cocok untuk alur kerja agen otonom, pemanggilan alat (tool calling), dan otomatisasi multi-langkah, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun Gemini 2.5 Flash (Sangat cocok untuk interaksi real-time dengan latensi sangat rendah dan routing bervolume tinggi, sistem RAG perusahaan, dan integrasi API skala produksi.) sangat tangguh: Gemini 2.5 Flash unggul dalam penalaran dan pemrograman, Gemini 2.5 Flash memberikan kecepatan generasi token lebih tinggi, dan Gemini 2.5 Flash lebih hemat biaya untuk penggunaan API skala besar.

Pertanyaan Umum (FAQ)

Mana yang lebih baik untuk coding dan penalaran, Gemini 2.5 Computer Use atau Gemini 2.5 Flash?+

Dalam indeks kecerdasan gabungan dan benchmark coding, Gemini 2.5 Flash memimpin. Lihat skor SWE-bench dan GPQA di atas untuk detailnya.

Berapa perbandingan harga API Gemini 2.5 Computer Use vs Gemini 2.5 Flash?+

Gemini 2.5 Computer Use mengenakan biaya $1.50 / $8.00 per 1M token input/output, sedangkan Gemini 2.5 Flash sebesar $0.30 / $2.50. Secara keseluruhan, Gemini 2.5 Flash lebih hemat biaya.

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

Gemini 2.5 Computer Use mendukung konteks 128K token dibandingkan 1.05M token pada Gemini 2.5 Flash, sementara Gemini 2.5 Flash 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)

Gemini 2.5 Computer Use vs Gemini 2.5 Flash

Ganti & Bandingkan Model Apa Saja

Gemini 2.5 Computer Use

Gemini 2.5 Flash

Siapa Unggul di Mana?

Skor Benchmark Terverifikasi

Latensi & Waktu Respons

Simulator Biaya Token Interaktif

Gemini 2.5 Computer Use · Strengths & Key Advantages

Considerations & Trade-offs

Gemini 2.5 Flash · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Spesifikasi Teknis

Gemini 2.5 Computer Use vs Gemini 2.5 Flash: Jawaban Cepat (FAQ)

Kesimpulan

Pertanyaan Umum (FAQ)

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