Head-to-Head Model Comparison

Sonar vs Gemini 1.5 Pro

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.

SonarProfile

Gemini 1.5 ProProfile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

Perplexity

Sonar

Model Ringan & Hemat Biaya

Sonar dari Perplexity adalah model AI yang dirancang untuk efisiensi biaya API maksimal per token dan throughput produksi yang ringan, menghadirkan jendela konteks 128K, kecepatan 130 token/detik, indeks kecerdasan 73/100, serta tarif $1/$1

Intelligence Index73 / 100

Input Token:

$1.00 / 1M

Output Token:

$1.00 / 1M

Context Window:

128K tokens

SWE-bench Verified:

N/A

Google

Gemini 1.5 Pro

Model Generasi Klasik

Gemini 1.5 Pro dari Google adalah model AI yang dirancang untuk asisten percakapan, peringkasan dokumen, dan beban kerja bisnis umum, menghadirkan jendela konteks 2M, kecepatan 65 token/detik, indeks kecerdasan 46/100, serta tarif $1.25/$5

Intelligence Index46 / 100

Input Token:

$1.25 / 1M

Output Token:

$5.00 / 1M

Context Window:

2M tokens

SWE-bench Verified:

32.5%

Perbedaan Utama Sekilas

Sonar is 2.7x cheaper for API usage (input + output tokens combined).
Gemini 1.5 Pro has a larger context window (2M vs 128K tokens).
Sonar is faster at 130 tok/s vs 65 tok/s.

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

Feature	Sonar	Gemini 1.5 Pro
Intelligence Index Composite reasoning & knowledge score (0-100)	73	46
Provider	Perplexity	Google
Input Price Cost per million input tokens	$1.00 / 1M	$1.25 / 1M
Output Price Cost per million output tokens	$1.00 / 1M	$5.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$0.37 / 1M	$0.97 / 1M
Context Window Maximum input + output tokens	128K tokens~192 A4 pages of text	2M tokens~3,000 A4 pages of text
Max Output Tokens Per single request	4K	8K
Throughput Speed Tokens generated per second	130 tok/s	65 tok/s
SWE-bench Verified Real-world software engineering	N/A	32.5%
GPQA Diamond Graduate-level reasoning	N/A	58.5%
Cached Input Price Prompt caching discount per 1M tokens	$0.10 / 1M	$0.31 / 1M

Siapa Unggul di Mana?

At-a-glance decision framework

Coding

Evaluations ongoing

Cost

Sonar

2.7x cheaper monthly runtime

Speed

Sonar

+100% faster generation

Context

Gemini 1.5 Pro

2M tokens window

Skor Benchmark Terverifikasi

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

SonarGemini 1.5 Pro

SWE-bench Verified (Autonomous Coding)

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

N/Avs32.5%

GPQA Diamond (Doctorate-Level Science & Math)

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

N/Avs58.5%

MMLU-Pro (Multi-task Language Understanding)

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

71%vs75.2%

LMSYS Chatbot Arena Elo

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

1245ptsvs1290pts

Long-Context Reasoning

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

N/Avs89.2%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

130 tok/s vs65 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

Sonar0.35s

Gemini 1.5 Pro0.80s

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

Sonar4.20s

Gemini 1.5 Pro8.49s

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)

Sonar Monthly API Bill

$2.55 / month

$1/1M in · $1/1M out

Gemini 1.5 Pro Monthly API Bill

$6.84 / month

$1.25/1M in · $5/1M out

Sonar saves approximately $4.29 / month (63%) under this workload.2.7x Savings

Sonar · Strengths & Key Advantages

Jendela konteks 128K dengan kapasitas output maksimum hingga 4K token (MMLU-Pro 71% · Arena Elo 1245)
Kecepatan generasi tinggi 130 token/detik dengan latensi token pertama (TTFT) hanya 350 ms
Skema harga API kompetitif (tarif $1/$1 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 1.5 Pro · Strengths & Key Advantages

Jendela konteks 2M dengan kapasitas output maksimum hingga 8K token (SWE-bench Verified 32.5% · GPQA Diamond 58.5%)
Kecepatan generasi tinggi 65 token/detik dengan latensi token pertama (TTFT) hanya 800 ms
Skema harga API kompetitif (tarif $1.25/$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	Sonar	Gemini 1.5 Pro
Cost per Task Estimated USD to finish one task	$0.05	$0.20
Output Tokens / Task Tokens generated per task	10K	24K
Reasoning Tokens / Task Thinking tokens burned per task	0K	0K

Spesifikasi Teknis

Architecture, release timeline, capabilities, and modalities.

Feature	Sonar	Gemini 1.5 Pro
Official API Model ID (SDK)	sonar	models/gemini-1-5-pro
API Protocol	Perplexity REST API (OpenAI-Compatible)	Google Gemini API (generateContent) + OpenAI-Compatible SDK
Release Date	2024-01	2024-02
Knowledge Cutoff	Real-time (Web-grounded)	May 2024
Architecture	Web-Search Augmented Autoregressive Transformer	Sparse Mixture-of-Experts (MoE) Multimodal
Parameters	Confidential / Llama 3 Fine-Tune	Confidential
Enterprise Rate Limits (RPM / TPM)	5,000 – 15,000 RPM (Production Tier) · 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 ($1/1M in) across full 128K window	Standard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTL	Cached input at $0.1/1M tokens	Implicit + Explicit Context Caching at $0.31/1M with configurable TTL
Computer Use / GUI Agent	API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)	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	Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools	Built-in Google Search Grounding + Managed Python Code Execution Sandbox
Official Fine-Tuning Support	API Prompt Engineering & RAG Distillation	Vertex AI Supervised Adapter Tuning & Context Distillation
Multimodal Token Billing	Text BPE (~4 chars/token)	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	Perplexity Production Safety & Alignment 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	text, vision, audio, video
Output Modalities	text	text

Sonar vs Gemini 1.5 Pro: Jawaban Cepat (FAQ)

Which is more intelligent, Sonar or Gemini 1.5 Pro?

Sonar is more intelligent. It scores 73 compared with 46 on the composite Intelligence Index.

Which model is faster?

Sonar is faster, generating 130 tokens per second compared with 65 tokens per second.

Which model is cheaper to run?

Sonar is cheaper at $0.37 per 1M tokens blended, compared with $0.97 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Sonar has lower latency, with a time to first token of 0.35s compared with 0.80s.

Which model has a larger context window?

Gemini 1.5 Pro has a larger context window, supporting 2M tokens compared with 128K tokens.

Kesimpulan

Baik Sonar (Sangat cocok untuk efisiensi biaya API maksimal per token dan throughput produksi yang ringan, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun Gemini 1.5 Pro (Sangat cocok untuk asisten percakapan, peringkasan dokumen, dan beban kerja bisnis umum, sistem RAG perusahaan, dan integrasi API skala produksi.) sangat tangguh: Sonar unggul dalam penalaran dan pemrograman, Sonar memberikan kecepatan generasi token lebih tinggi, dan Sonar lebih hemat biaya untuk penggunaan API skala besar.

Pertanyaan Umum (FAQ)

Mana yang lebih baik untuk coding dan penalaran, Sonar atau Gemini 1.5 Pro?+

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

Berapa perbandingan harga API Sonar vs Gemini 1.5 Pro?+

Sonar mengenakan biaya $1.00 / $1.00 per 1M token input/output, sedangkan Gemini 1.5 Pro sebesar $1.25 / $5.00. Secara keseluruhan, Sonar lebih hemat biaya.

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

Sonar mendukung konteks 128K token dibandingkan 2M token pada Gemini 1.5 Pro, sementara Sonar 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)

Sonar vs Gemini 1.5 Pro

Ganti & Bandingkan Model Apa Saja

Sonar

Gemini 1.5 Pro

Siapa Unggul di Mana?

Skor Benchmark Terverifikasi

Latensi & Waktu Respons

Simulator Biaya Token Interaktif

Sonar · Strengths & Key Advantages

Considerations & Trade-offs

Gemini 1.5 Pro · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Spesifikasi Teknis

Sonar vs Gemini 1.5 Pro: Jawaban Cepat (FAQ)

Kesimpulan

Pertanyaan Umum (FAQ)

Related reading