Head-to-Head Model Comparison

Amazon Nova Lite vs GPT-6.1 Sol

Benchmarks, API Token Pricing, Context Window & Speed Comparison

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

Compare Amazon Nova Lite by Amazon against GPT-6.1 Sol by OpenAI across real-world coding, reasoning, token economics, and latency.

Confronto Diretto (VS)

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Popular Matchups:
Amazon

Amazon Nova Lite

Modello IA ad Alte Prestazioni

Amazon Nova Lite di Amazon è un modello di intelligenza artificiale con finestra di contesto da 300K token e tariffazione API di $0.06/1M token in input e $0.24/1M in output, ideale per coding, ragionamento e automazione aziendale.

Intelligence Index38 / 100
Input Token:

$0.06 / 1M

Output Token:

$0.24 / 1M

Context Window:

300K tokens

SWE-bench Verified:

31.2%

OpenAI

GPT-6.1 Sol

Modello di Ragionamento Profondo

GPT-6.1 Sol di OpenAI è un modello di intelligenza artificiale con finestra di contesto da 1M token e tariffazione API di $2.0/1M token in input e $10.0/1M in output, ideale per coding, ragionamento e automazione aziendale.

Intelligence Index94 / 100
Input Token:

$2.00 / 1M

Output Token:

$10.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

82.3%

Differenze Chiave a Colpo d’Occhio

  • Amazon Nova Lite is 37.0x cheaper for API usage (input + output tokens combined).
  • GPT-6.1 Sol has a larger context window (1M vs 300K tokens).
  • Amazon Nova Lite is faster at 135 tok/s vs 120 tok/s.
  • GPT-6.1 Sol leads on SWE-bench coding (82.3% vs 31.2%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureAmazon Nova LiteGPT-6.1 Sol
Intelligence Index
Composite reasoning & knowledge score (0-100)
3894
Provider
AmazonOpenAI
Input Price
Cost per million input tokens
$0.06 / 1M$2.00 / 1M
Output Price
Cost per million output tokens
$0.24 / 1M$10.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.05 / 1M$1.47 / 1M
Context Window
Maximum input + output tokens
300K tokens~450 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
8K128K
Throughput Speed
Tokens generated per second
135 tok/s120 tok/s
SWE-bench Verified
Real-world software engineering
31.2%82.3%
GPQA Diamond
Graduate-level reasoning
42%80.8%
Cached Input Price
Prompt caching discount per 1M tokens
$0.01 / 1M$0.10 / 1M

Chi vince in ogni categoria?

At-a-glance decision framework
Coding
GPT-6.1 Sol
+51.1% SWE-bench lead
Cost
Amazon Nova Lite
37.0x cheaper monthly runtime
Speed
Amazon Nova Lite
+13% faster generation
Context
GPT-6.1 Sol
1M tokens window

Punteggi Benchmark Verificati

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

Amazon Nova LiteGPT-6.1 Sol
SWE-bench Verified (Autonomous Coding)

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

31.2%vs82.3%
GPQA Diamond (Doctorate-Level Science & Math)

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

42%vs80.8%
MMLU-Pro (Multi-task Language Understanding)

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

61.2%vs89.9%
LMSYS Chatbot Arena Elo

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

1230ptsvs1519pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

4%vs18.1%
Terminal-Bench (Agentic Coding & Terminal Use)

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

20.5%vs63.6%
SciCode (Scientific Computing)

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

21%vs54.8%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

34.2%vs79.7%
AIME (Advanced Math Competition)

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

39.5%vs93.5%
Long-Context Reasoning

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

66%vs91%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

135 tok/s vs120 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
Amazon Nova Lite0.28s
GPT-6.1 Sol1.12s
Est. End-to-End Response (500 tokens)TTFT + generation time
Amazon Nova Lite3.98s
GPT-6.1 Sol5.29s

Simulatore Interattivo dei Costi Token

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

100K / day
10K500K1M
30K / day
5K150K300K
50% cached
0% (Cold)50%90% (Warm)
Amazon Nova Lite Monthly API Bill
$0.33 / month
$0.06/1M in · $0.24/1M out
GPT-6.1 Sol Monthly API Bill
$12.15 / month
$2/1M in · $10/1M out
Amazon Nova Lite saves approximately $11.82 / month (97%) under this workload.37.0x Savings

Amazon Nova Lite · Strengths & Key Advantages

  • Architettura High-Speed Multimodal Foundation Transformer avanzata di Amazon con supporto fino a 300K token di contesto
  • Ottimo rapporto qualità-prezzo ($0.06/1M input, $0.24/1M output) e bassa latenza
  • Elevate prestazioni nei benchmark di programmazione, logica e comprensione multilingue
Considerations & Trade-offs
  • L'utilizzo intensivo di contesti molto ampi richiede un attento monitoraggio dei costi dei token
  • Per casi d'uso verticali complessi è consigliabile un prompt engineering mirato

GPT-6.1 Sol · Strengths & Key Advantages

  • Architettura Near-Astra unified reasoning model avanzata di OpenAI con supporto fino a 1M token di contesto
  • Ottimo rapporto qualità-prezzo ($2.0/1M input, $10.0/1M output) e bassa latenza
  • Elevate prestazioni nei benchmark di programmazione, logica e comprensione multilingue
Considerations & Trade-offs
  • L'utilizzo intensivo di contesti molto ampi richiede un attento monitoraggio dei costi dei token
  • Per casi d'uso verticali complessi è consigliabile un prompt engineering mirato

Token Use & Task Economics

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

MetricAmazon Nova LiteGPT-6.1 Sol
Cost per Task
Estimated USD to finish one task
$0.06$2.05
Output Tokens / Task
Tokens generated per task
19K62K
Reasoning Tokens / Task
Thinking tokens burned per task
0K36K

Specifiche Tecniche

Architecture, release timeline, capabilities, and modalities.

FeatureAmazon Nova LiteGPT-6.1 Sol
Official API Model ID (SDK)nova-litegpt-6-1-sol
API ProtocolAmazon REST API (OpenAI-Compatible)OpenAI Responses API & Chat Completions v1
Release Date2024-122026-09
Knowledge CutoffOctober 2024April 2026
ArchitectureHigh-Speed Multimodal Foundation TransformerNear-Astra unified reasoning model
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($0.06/1M in) across full 300K windowFlat rate ($2/1M in) across full 1000K window
Prompt Cache Policy & TTLCached input at $0.015/1M tokensAutomatic prefix caching at $0.1/1M (no extra cache-write fee)
Computer Use / GUI AgentAPI / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)Supported (Screen coordinate grounding, browser & desktop GUI action loops)
MCP & Parallel Tool CallingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON SchemaNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & SandboxSupported via external Tavily/Exa Search & E2B/Docker Sandbox toolsNative Web Search tool + Hosted Code Interpreter & File Search RAG
Official Fine-Tuning SupportAPI Prompt Engineering & RAG DistillationSupervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)
Multimodal Token BillingText BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Video (~258–300 tokens/sec)Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)
Quantization & Min GPU VRAMCloud-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 ClassificationAmazon Production Safety & Alignment VerifiedOpenAI Preparedness Framework Audited & System Card Published
Enterprise Compliance (ZDR/HIPAA/SOC2)SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise TierSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestext, vision, videotext, vision
Output Modalitiestexttext

Amazon Nova Lite vs GPT-6.1 Sol: Risposte Rapide (FAQ)

Which is more intelligent, Amazon Nova Lite or GPT-6.1 Sol?

GPT-6.1 Sol is more intelligent. It scores 94 compared with 38 on the composite Intelligence Index.

Which model is faster?

Amazon Nova Lite is faster, generating 135 tokens per second compared with 120 tokens per second.

Which model is cheaper to run?

Amazon Nova Lite is cheaper at $0.05 per 1M tokens blended, compared with $1.47 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Amazon Nova Lite has lower latency, with a time to first token of 0.28s 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 300K tokens.

Verdetto

Choose Amazon Nova Lite for automazione enterprise, sviluppo software, agenti ia autonomi e pipeline di produzione amazon, or choose GPT-6.1 Sol for automazione enterprise, sviluppo software, agenti ia autonomi e pipeline di produzione openai.

Domande Frequenti (FAQ)

Which is cheaper: Amazon Nova Lite or GPT-6.1 Sol?+

Amazon Nova Lite costs $0.06/1M input and $0.24/1M output tokens, while GPT-6.1 Sol costs $2/1M input and $10/1M output tokens.

Which model has a larger context window: Amazon Nova Lite or GPT-6.1 Sol?+

Amazon Nova Lite supports 300K tokens whereas GPT-6.1 Sol supports 1M tokens.

AI Terminology & Guide
Explore Glossary →

Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.

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.

Fonti ufficiali: Amazon & OpenAI Official Documentation