Sonar vs GPT-6.1 Sol
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare Sonar by Perplexity against GPT-6.1 Sol by OpenAI across real-world coding, reasoning, token economics, and latency.
किसी भी मॉडल को बदलें और तुलना करें
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Live comparison: no in-depth editorial review has been published for this pair yet.
Sonar
उच्च-प्रदर्शन AI मॉडलPerplexity द्वारा विकसित Sonar एक उन्नत AI मॉडल है, जिसमें 128K टोकन का कॉन्टेक्स्ट विंडो और $1/1M इनपुट तथा $1/1M आउटपुट मूल्य निर्धारण है। यह कोडिंग, विश्लेषण और एंटरप्राइज वर्कफ़्लो के लिए उपयुक्त है।
$1.00 / 1M
$1.00 / 1M
128K tokens
N/A
GPT-6.1 Sol
डीप रीजनिंग मॉडलOpenAI द्वारा विकसित GPT-6.1 Sol एक उन्नत AI मॉडल है, जिसमें 1M टोकन का कॉन्टेक्स्ट विंडो और $2.0/1M इनपुट तथा $10.0/1M आउटपुट मूल्य निर्धारण है। यह कोडिंग, विश्लेषण और एंटरप्राइज वर्कफ़्लो के लिए उपयुक्त है।
$2.00 / 1M
$10.00 / 1M
1M tokens
82.3%
एक नज़र में मुख्य अंतर
- Sonar is 4.8x cheaper for API usage (input + output tokens combined).
- GPT-6.1 Sol has a larger context window (1M vs 128K tokens).
- Sonar is faster at 130 tok/s vs 120 tok/s.
| Feature | Sonar | GPT-6.1 Sol |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 73 | 94 |
Provider | Perplexity | OpenAI |
Input Price Cost per million input tokens | $1.00 / 1M | $2.00 / 1M |
Output Price Cost per million output tokens | $1.00 / 1M | $10.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.37 / 1M | $1.47 / 1M |
Context Window Maximum input + output tokens | 128K tokens~192 A4 pages of text | 1M tokens~1,500 A4 pages of text |
Max Output Tokens Per single request | 4K | 128K |
Throughput Speed Tokens generated per second | 130 tok/s | 120 tok/s |
SWE-bench Verified Real-world software engineering | N/A | 82.3% |
GPQA Diamond Graduate-level reasoning | N/A | 80.8% |
Cached Input Price Prompt caching discount per 1M tokens | $0.10 / 1M | $0.10 / 1M |
किस क्षेत्र में कौन आगे है?
At-a-glance decision frameworkEvaluations ongoing
सत्यापित बेंचमार्क स्कोर तुलना
Official evaluation metrics verified by independent third-party research labs.
Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.
Challenging questions created by domain experts to test complex PhD-level reasoning.
Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.
Crowdsourced human preference evaluation based on blind, head-to-head model battles.
Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
Research-grade coding problems drawn from real scientific and numerical workloads.
Contamination-free competitive programming problems collected continuously over time.
American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.
Accuracy when reasoning over very large inputs that fill the model context window.
Tokens emitted per second during active generation streaming.
लेटेंसी और रिस्पॉन्स समय
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
रियल-टाइम टोकन लागत सिम्युलेटर
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Sonar · Strengths & Key Advantages
- Perplexity की उन्नत Web-Search Augmented Autoregressive Transformer आर्किटेक्चर और 128K कॉन्टेक्स्ट विंडो क्षमता
- किफायती और पारदर्शी API मूल्य ($1/1M इनपुट, $1/1M आउटपुट) तेज़ रिस्पॉन्स के साथ
- जटिल कोडिंग, तार्किक विश्लेषण और बहुभाषी कार्यों में उच्च सटीकता
Considerations & Trade-offs
- बड़े पैमाने पर लंबे कॉन्टेक्स्ट प्रॉम्प्ट्स के लिए टोकन बजट प्रबंधन आवश्यक है
- विशिष्ट डोमेन कार्यों में सर्वोत्तम परिणाम के लिए सटीक प्रॉम्प्ट इंजीनियरिंग की आवश्यकता होती है
GPT-6.1 Sol · Strengths & Key Advantages
- OpenAI की उन्नत Near-Astra unified reasoning model आर्किटेक्चर और 1M कॉन्टेक्स्ट विंडो क्षमता
- किफायती और पारदर्शी API मूल्य ($2.0/1M इनपुट, $10.0/1M आउटपुट) तेज़ रिस्पॉन्स के साथ
- जटिल कोडिंग, तार्किक विश्लेषण और बहुभाषी कार्यों में उच्च सटीकता
Considerations & Trade-offs
- बड़े पैमाने पर लंबे कॉन्टेक्स्ट प्रॉम्प्ट्स के लिए टोकन बजट प्रबंधन आवश्यक है
- विशिष्ट डोमेन कार्यों में सर्वोत्तम परिणाम के लिए सटीक प्रॉम्प्ट इंजीनियरिंग की आवश्यकता होती है
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Sonar | GPT-6.1 Sol |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.05 | $2.05 |
Output Tokens / Task Tokens generated per task | 10K | 62K |
Reasoning Tokens / Task Thinking tokens burned per task | 0K | 36K |
तकनीकी विशिष्टताएँ (Specs)
Architecture, release timeline, capabilities, and modalities.
| Feature | Sonar | GPT-6.1 Sol |
|---|---|---|
| Official API Model ID (SDK) | sonar | gpt-6-1-sol |
| API Protocol | Perplexity REST API (OpenAI-Compatible) | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2024-01 | 2026-09 |
| Knowledge Cutoff | Real-time (Web-grounded) | April 2026 |
| Architecture | Web-Search Augmented Autoregressive Transformer | Near-Astra unified reasoning model |
| 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 | Flat rate ($2/1M in) across full 1000K window |
| Prompt Cache Policy & TTL | Cached input at $0.1/1M tokens | Automatic prefix caching at $0.1/1M (no extra cache-write fee) |
| 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 | Native Web Search tool + Hosted Code Interpreter & File Search RAG |
| Official Fine-Tuning Support | API Prompt Engineering & RAG Distillation | Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT) |
| Multimodal Token Billing | Text BPE (~4 chars/token) | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) |
| 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 | OpenAI Preparedness Framework Audited & System Card Published |
| 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 |
| Output Modalities | text | text |
Sonar vs GPT-6.1 Sol: त्वरित प्रश्नोत्तर (FAQ)
Which is more intelligent, Sonar or GPT-6.1 Sol?
GPT-6.1 Sol is more intelligent. It scores 94 compared with 73 on the composite Intelligence Index.
Which model is faster?
Sonar is faster, generating 130 tokens per second compared with 120 tokens per second.
Which model is cheaper to run?
Sonar is cheaper at $0.37 per 1M tokens blended, compared with $1.47 (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 1.12s.
Which model has a larger context window?
GPT-6.1 Sol has a larger context window, supporting 1M tokens compared with 128K tokens.
निष्कर्ष
Choose Sonar for एंटरप्राइज ऑटोमेशन, सॉफ्टवेयर डेवलपमेंट, ai एजेंट्स और perplexity आधारित प्रोडक्शन सिस्टम, or choose GPT-6.1 Sol for एंटरप्राइज ऑटोमेशन, सॉफ्टवेयर डेवलपमेंट, ai एजेंट्स और openai आधारित प्रोडक्शन सिस्टम.
अक्सर पूछे जाने वाले प्रश्न (FAQ)
Which is cheaper: Sonar or GPT-6.1 Sol?+
Sonar costs $1/1M input and $1/1M output tokens, while GPT-6.1 Sol costs $2/1M input and $10/1M output tokens.
Which model has a larger context window: Sonar or GPT-6.1 Sol?+
Sonar supports 128K tokens whereas GPT-6.1 Sol supports 1M tokens.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
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Benchmark scores, token prices, and rate limits evolve rapidly as AI labs release model updates. Always verify current specifications and pricing on the official provider documentation.
स्रोत: Perplexity & OpenAI Official Documentation