Head-to-Head Model Comparison

GPT-6.1 Sol vs GPT-6 Astra

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Verificato dal team di ricerca di GetInfoUsUltima verifica: October 2026Politica editoriale

Cambia e Confronta Qualsiasi Modello

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

GPT-6.1 SolProfile

GPT-6 AstraProfile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

OpenAI

GPT-6.1 Sol

Modello Ammiraglia di Frontiera

GPT-6.1 Sol di OpenAI è un modello di IA progettato per il ragionamento aziendale di frontiera, la programmazione avanzata e i carichi di produzione, con finestra di contesto da 1M, velocità di 120 token/s, indice di intelligenza di 94/100

Intelligence Index94 / 100

Input Token:

$2.00 / 1M

Output Token:

$10.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

82.3%

OpenAI

GPT-6 Astra

Modello Vocale e Audio Nativo

GPT-6 Astra di OpenAI è un modello di IA progettato per la sintesi vocale naturale, l’elaborazione audio in tempo reale e la trascrizione, con finestra di contesto da 272K, velocità di 100 token/s, indice di intelligenza di 96/100 e tariffa

Intelligence Index96 / 100

Input Token:

$10.00 / 1M

Output Token:

$50.00 / 1M

Context Window:

272K tokens

SWE-bench Verified:

82.4%

Differenze Chiave a Colpo d’Occhio

GPT-6.1 Sol is 5.1x cheaper for API usage (input + output tokens combined).
GPT-6.1 Sol has a larger context window (1M vs 272K tokens).
GPT-6.1 Sol is faster at 120 tok/s vs 100 tok/s.
GPT-6 Astra leads on SWE-bench coding (82.4% vs 82.3%).

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

Feature	GPT-6.1 Sol	GPT-6 Astra
Intelligence Index Composite reasoning & knowledge score (0-100)	94	96
Provider	OpenAI	OpenAI
Input Price Cost per million input tokens	$2.00 / 1M	$10.00 / 1M
Output Price Cost per million output tokens	$10.00 / 1M	$50.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$1.47 / 1M	$7.70 / 1M
Context Window Maximum input + output tokens	1M tokens~1,500 A4 pages of text	272K tokens~408 A4 pages of text
Max Output Tokens Per single request	128K	128K
Throughput Speed Tokens generated per second	120 tok/s	100 tok/s
SWE-bench Verified Real-world software engineering	82.3%	82.4%
GPQA Diamond Graduate-level reasoning	80.8%	80.9%
Cached Input Price Prompt caching discount per 1M tokens	$0.10 / 1M	$1.00 / 1M

Chi vince in ogni categoria?

At-a-glance decision framework

Coding

GPT-6 Astra

+0.1% SWE-bench lead

Cost

GPT-6.1 Sol

5.1x cheaper monthly runtime

Speed

GPT-6.1 Sol

+20% faster generation

Context

GPT-6.1 Sol

1M tokens window

Punteggi Benchmark Verificati

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

GPT-6.1 SolGPT-6 Astra

SWE-bench Verified (Autonomous Coding)

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

82.3%vs82.4%

GPQA Diamond (Doctorate-Level Science & Math)

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

80.8%vs80.9%

MMLU-Pro (Multi-task Language Understanding)

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

89.9%vs89.9%

LMSYS Chatbot Arena Elo

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

1519ptsvs1520pts

Humanity's Last Exam (Frontier Expert Knowledge)

Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.

18.1%vs18.2%

Terminal-Bench (Agentic Coding & Terminal Use)

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

63.6%vs63.8%

SciCode (Scientific Computing)

Research-grade coding problems drawn from real scientific and numerical workloads.

54.8%vs54.9%

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

79.7%vs79.8%

AIME (Advanced Math Competition)

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

93.5%vs93.6%

Long-Context Reasoning

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

91%vs91.2%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

120 tok/s vs100 tok/s

Latenza e Tempo di Risposta

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

GPT-6.1 Sol1.12s

GPT-6 Astra0.95s

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

GPT-6.1 Sol5.29s

GPT-6 Astra5.95s

Simulatore Interattivo dei Costi Token

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)

GPT-6.1 Sol Monthly API Bill

$12.15 / month

$2/1M in · $10/1M out

GPT-6 Astra Monthly API Bill

$61.50 / month

$10/1M in · $50/1M out

GPT-6.1 Sol saves approximately $49.35 / month (80%) under this workload.5.1x Savings

GPT-6.1 Sol · Strengths & Key Advantages

Finestra di contesto da 1M con capacità massima di output fino a 128K token (SWE-bench Verified 82.3% · GPQA Diamond 80.8%)
Throughput elevato di 120 token/secondo con latenza al primo token (TTFT) di soli 1120 ms
Economia API competitiva ($2/$10 per 1M di token) con supporto per prompt caching, tool calling e output JSON strutturati

Considerations & Trade-offs

Modello cloud proprietario chiuso; non consente il download locale dei pesi per l’esecuzione offline
Per volumi di traffico elevati in produzione si consiglia di attivare il prompt caching e la Batch API

GPT-6 Astra · Strengths & Key Advantages

Finestra di contesto da 272K con capacità massima di output fino a 128K token (SWE-bench Verified 82.4% · GPQA Diamond 80.9%)
Throughput elevato di 100 token/secondo con latenza al primo token (TTFT) di soli 950 ms
Economia API competitiva ($10/$50 per 1M di token) con supporto per prompt caching, tool calling e output JSON strutturati

Considerations & Trade-offs

Modello cloud proprietario chiuso; non consente il download locale dei pesi per l’esecuzione offline
Per volumi di traffico elevati in produzione si consiglia di attivare il prompt caching e la Batch API

Token Use & Task Economics

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

Metric	GPT-6.1 Sol	GPT-6 Astra
Cost per Task Estimated USD to finish one task	$2.05	$2.15
Output Tokens / Task Tokens generated per task	62K	58K
Reasoning Tokens / Task Thinking tokens burned per task	36K	32K

Specifiche Tecniche

Architecture, release timeline, capabilities, and modalities.

Feature	GPT-6.1 Sol	GPT-6 Astra
Official API Model ID (SDK)	gpt-6-1-sol	gpt-6-astra
API Protocol	OpenAI Responses API & Chat Completions v1	OpenAI Responses API & Chat Completions v1
Release Date	2026-09	2026-09
Knowledge Cutoff	April 2026	June 2026
Architecture	Near-Astra unified reasoning model	Omni-Adaptive Autoregressive with Dynamic CoT
Parameters	Confidential	Confidential
Enterprise Rate Limits (RPM / TPM)	10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM	10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)	Flat rate ($2/1M in) across full 1000K window	Flat rate ($10/1M in) across full 272K window
Prompt Cache Policy & TTL	Automatic prefix caching at $0.1/1M (no extra cache-write fee)	Automatic prefix caching at $1/1M (no extra cache-write fee)
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	Native Web Search tool + Hosted Code Interpreter & File Search RAG	Native Web Search tool + Hosted Code Interpreter & File Search RAG
Official Fine-Tuning Support	Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)	Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)
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)
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	OpenAI Preparedness Framework Audited & System Card Published	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, vision	text, vision, audio
Output Modalities	text	text, audio

GPT-6.1 Sol vs GPT-6 Astra: Risposte Rapide (FAQ)

Which is more intelligent, GPT-6.1 Sol or GPT-6 Astra?

GPT-6 Astra is more intelligent. It scores 96 compared with 94 on the composite Intelligence Index.

Which model is faster?

GPT-6.1 Sol is faster, generating 120 tokens per second compared with 100 tokens per second.

Which model is cheaper to run?

GPT-6.1 Sol is cheaper at $1.47 per 1M tokens blended, compared with $7.70 (7:2:1 cache:input:output ratio).

Which model has lower latency?

GPT-6 Astra has lower latency, with a time to first token of 0.95s 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 272K tokens.

Verdetto

Sia GPT-6.1 Sol (Ideale per il ragionamento aziendale di frontiera, la programmazione avanzata e i carichi di produzione, sistemi RAG aziendali e integrazioni API scalabili.) sia GPT-6 Astra (Ideale per la sintesi vocale naturale, l’elaborazione audio in tempo reale e la trascrizione, sistemi RAG aziendali e integrazioni API scalabili.) eccellono in produzione: GPT-6 Astra guida nei benchmark di ragionamento e programmazione, GPT-6.1 Sol garantisce una generazione più rapida e GPT-6.1 Sol offre il miglior rapporto qualità-prezzo per carichi API elevati.

Domande Frequenti (FAQ)

Quale modello è migliore per coding e ragionamento, GPT-6.1 Sol o GPT-6 Astra?+

Nell’indice di intelligenza composito e nei benchmark di programmazione prevale GPT-6 Astra. Consulta i punteggi SWE-bench e GPQA qui sopra per tutti i dettagli.

Qual è la differenza di prezzo API tra GPT-6.1 Sol e GPT-6 Astra?+

GPT-6.1 Sol costa $2.00 / $10.00 per milione di token di input/output, mentre GPT-6 Astra costa $10.00 / $50.00. Nel costo combinato, GPT-6.1 Sol risulta più economico.

Quale modello ha la finestra di contesto più ampia e la velocità maggiore?+

GPT-6.1 Sol supporta 1M token di contesto contro 272K token di GPT-6 Astra, mentre GPT-6.1 Sol offre una velocità di generazione superiore.

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)

GPT-6.1 Sol vs GPT-6 Astra

Cambia e Confronta Qualsiasi Modello

GPT-6.1 Sol

GPT-6 Astra

Chi vince in ogni categoria?

Punteggi Benchmark Verificati

Latenza e Tempo di Risposta

Simulatore Interattivo dei Costi Token

GPT-6.1 Sol · Strengths & Key Advantages

Considerations & Trade-offs

GPT-6 Astra · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Specifiche Tecniche

GPT-6.1 Sol vs GPT-6 Astra: Risposte Rapide (FAQ)

Verdetto

Domande Frequenti (FAQ)

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