Head-to-Head Model Comparison

Amazon Nova Micro 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 Micro 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 Micro

Modello IA ad Alte Prestazioni

Amazon Nova Micro di Amazon è un modello di intelligenza artificiale con finestra di contesto da 128K token e tariffazione API di $0.035/1M token in input e $0.14/1M in output, ideale per coding, ragionamento e automazione aziendale.

Intelligence Index34 / 100
Input Token:

$0.04 / 1M

Output Token:

$0.14 / 1M

Context Window:

128K tokens

SWE-bench Verified:

23%

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 Micro is 63.3x cheaper for API usage (input + output tokens combined).
  • GPT-6.1 Sol has a larger context window (1M vs 128K tokens).
  • Amazon Nova Micro is faster at 175 tok/s vs 120 tok/s.
  • GPT-6.1 Sol leads on SWE-bench coding (82.3% vs 23.0%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureAmazon Nova MicroGPT-6.1 Sol
Intelligence Index
Composite reasoning & knowledge score (0-100)
3494
Provider
AmazonOpenAI
Input Price
Cost per million input tokens
$0.04 / 1M$2.00 / 1M
Output Price
Cost per million output tokens
$0.14 / 1M$10.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.03 / 1M$1.47 / 1M
Context Window
Maximum input + output tokens
128K tokens~192 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
8K128K
Throughput Speed
Tokens generated per second
175 tok/s120 tok/s
SWE-bench Verified
Real-world software engineering
23%82.3%
GPQA Diamond
Graduate-level reasoning
33.5%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
+59.3% SWE-bench lead
Cost
Amazon Nova Micro
63.3x cheaper monthly runtime
Speed
Amazon Nova Micro
+46% 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 MicroGPT-6.1 Sol
SWE-bench Verified (Autonomous Coding)

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

23%vs82.3%
GPQA Diamond (Doctorate-Level Science & Math)

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

33.5%vs80.8%
MMLU-Pro (Multi-task Language Understanding)

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

52%vs89.9%
LMSYS Chatbot Arena Elo

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

1195ptsvs1519pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

2.8%vs18.1%
Terminal-Bench (Agentic Coding & Terminal Use)

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

15.2%vs63.6%
SciCode (Scientific Computing)

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

16%vs54.8%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

26%vs79.7%
AIME (Advanced Math Competition)

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

30.5%vs93.5%
Long-Context Reasoning

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

60%vs91%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

175 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 Micro0.18s
GPT-6.1 Sol1.12s
Est. End-to-End Response (500 tokens)TTFT + generation time
Amazon Nova Micro3.04s
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 Micro Monthly API Bill
$0.19 / month
$0.035/1M in · $0.14/1M out
GPT-6.1 Sol Monthly API Bill
$12.15 / month
$2/1M in · $10/1M out
Amazon Nova Micro saves approximately $11.96 / month (98%) under this workload.63.3x Savings

Amazon Nova Micro · Strengths & Key Advantages

  • Architettura Ultra-Fast Text-Only Dense Transformer avanzata di Amazon con supporto fino a 128K token di contesto
  • Ottimo rapporto qualità-prezzo ($0.035/1M input, $0.14/1M 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 MicroGPT-6.1 Sol
Cost per Task
Estimated USD to finish one task
$0.03$2.05
Output Tokens / Task
Tokens generated per task
15K62K
Reasoning Tokens / Task
Thinking tokens burned per task
0K36K

Specifiche Tecniche

Architecture, release timeline, capabilities, and modalities.

FeatureAmazon Nova MicroGPT-6.1 Sol
Official API Model ID (SDK)nova-microgpt-6-1-sol
API ProtocolAmazon REST API (OpenAI-Compatible)OpenAI Responses API & Chat Completions v1
Release Date2024-122026-09
Knowledge CutoffOctober 2024April 2026
ArchitectureUltra-Fast Text-Only Dense 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 ($0.035/1M in) across full 128K windowFlat rate ($2/1M in) across full 1000K window
Prompt Cache Policy & TTLCached input at $0.009/1M 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)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 Modalitiestexttext, vision
Output Modalitiestexttext

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

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

GPT-6.1 Sol is more intelligent. It scores 94 compared with 34 on the composite Intelligence Index.

Which model is faster?

Amazon Nova Micro is faster, generating 175 tokens per second compared with 120 tokens per second.

Which model is cheaper to run?

Amazon Nova Micro is cheaper at $0.03 per 1M tokens blended, compared with $1.47 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Amazon Nova Micro has lower latency, with a time to first token of 0.18s 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.

Verdetto

Choose Amazon Nova Micro 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 Micro or GPT-6.1 Sol?+

Amazon Nova Micro costs $0.035/1M input and $0.14/1M 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 Micro or GPT-6.1 Sol?+

Amazon Nova Micro supports 128K 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