Head-to-Head Model Comparison

Qwen3.7 Max vs Qwen3.6 Max Preview

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Verificato dal team di ricerca di GetInfoUsUltima verifica: October 2026Politica editoriale
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Related topics (12)
AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Qwen3.7 Max vs Qwen3.6 Max Preview: Benchmarks, Pricing & Speed Comparison

Qwen3.7 Max di Alibaba e Qwen3.6 Max Preview di Alibaba sono due modelli di IA di riferimento. Qwen3.7 Max offre una finestra di contesto di 1M token a $1.80/$7.20 per milione di token, mentre Qwen3.6 Max Preview mette a disposizione 262.1K token di contesto a $1.50/$6.00 per milione di token. Di seguito analizziamo benchmark, latenza e costi.

Confronto Diretto (VS)

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Alibaba

Qwen3.7 Max

IA Agentica e Strumenti Autonomi

Qwen3.7 Max di Alibaba è un modello di IA progettato per i workflow agentici autonomi, il tool calling e l’automazione multi-step, con finestra di contesto da 1M, velocità di 80 token/s, indice di intelligenza di 92/100 e tariffa di $1.8/$7

Intelligence Index92 / 100
Input Token:

$1.80 / 1M

Output Token:

$7.20 / 1M

Context Window:

1M tokens

SWE-bench Verified:

73.5%

Alibaba

Qwen3.6 Max Preview

Modello Ammiraglia di Frontiera

Qwen3.6 Max Preview di Alibaba 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 262K, velocità di 75 token/s, indice di intelligenza

Intelligence Index90 / 100
Input Token:

$1.50 / 1M

Output Token:

$6.00 / 1M

Context Window:

262.1K tokens

SWE-bench Verified:

70%

Differenze Chiave a Colpo d’Occhio

  • Qwen3.6 Max Preview is 1.2x cheaper for API usage (input + output tokens combined).
  • Qwen3.7 Max has a larger context window (1M vs 262K tokens).
  • Qwen3.7 Max is faster at 80 tok/s vs 75 tok/s.
  • Qwen3.7 Max leads on SWE-bench coding (73.5% vs 70.0%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureQwen3.7 MaxQwen3.6 Max Preview
Intelligence Index
Composite reasoning & knowledge score (0-100)
9290
Provider
AlibabaAlibaba
Input Price
Cost per million input tokens
$1.80 / 1M$1.50 / 1M
Output Price
Cost per million output tokens
$7.20 / 1M$6.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$1.21 / 1M$1.01 / 1M
Context Window
Maximum input + output tokens
1M tokens~1,500 A4 pages of text262.1K tokens~393 A4 pages of text
Max Output Tokens
Per single request
32K16K
Throughput Speed
Tokens generated per second
80 tok/s75 tok/s
SWE-bench Verified
Real-world software engineering
73.5%70%
GPQA Diamond
Graduate-level reasoning
78.5%76%
Cached Input Price
Prompt caching discount per 1M tokens
$0.18 / 1M$0.15 / 1M

Chi vince in ogni categoria?

At-a-glance decision framework
Coding
Qwen3.7 Max
+3.5% SWE-bench lead
Cost
Qwen3.6 Max Preview
1.2x cheaper monthly runtime
Speed
Qwen3.7 Max
+7% faster generation
Context
Qwen3.7 Max
1M tokens window

Punteggi Benchmark Verificati

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

Qwen3.7 MaxQwen3.6 Max Preview
SWE-bench Verified (Autonomous Coding)

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

73.5%vs70%
GPQA Diamond (Doctorate-Level Science & Math)

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

78.5%vs76%
MMLU-Pro (Multi-task Language Understanding)

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

88.5%vs87.5%
LMSYS Chatbot Arena Elo

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

1470ptsvs1445pts
AIME (Advanced Math Competition)

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

86%vsN/A
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

80 tok/s vs75 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
Qwen3.7 Max0.58s
Qwen3.6 Max Preview0.54s
Est. End-to-End Response (500 tokens)TTFT + generation time
Qwen3.7 Max6.83s
Qwen3.6 Max Preview7.21s

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)
Qwen3.7 Max Monthly API Bill
$9.45 / month
$1.8/1M in · $7.2/1M out
Qwen3.6 Max Preview Monthly API Bill
$7.88 / month
$1.5/1M in · $6/1M out
Qwen3.6 Max Preview saves approximately $1.58 / month (17%) under this workload.1.2x Savings

Qwen3.7 Max · Strengths & Key Advantages

  • Finestra di contesto da 1M con capacità massima di output fino a 32K token (SWE-bench Verified 73.5% · GPQA Diamond 78.5%)
  • Throughput elevato di 80 token/secondo con latenza al primo token (TTFT) di soli 580 ms
  • Economia API competitiva ($1.8/$7.2 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
  • Nelle dimostrazioni scientifiche più estreme, i modelli di ragionamento pesante dedicati offrono maggiore profondità

Qwen3.6 Max Preview · Strengths & Key Advantages

  • Finestra di contesto da 262K con capacità massima di output fino a 16K token (SWE-bench Verified 70% · GPQA Diamond 76%)
  • Throughput elevato di 75 token/secondo con latenza al primo token (TTFT) di soli 540 ms
  • Economia API competitiva ($1.5/$6 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
  • Nelle dimostrazioni scientifiche più estreme, i modelli di ragionamento pesante dedicati offrono maggiore profondità

Token Use & Task Economics

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

MetricQwen3.7 MaxQwen3.6 Max Preview
Cost per Task
Estimated USD to finish one task
$0.38$0.32
Output Tokens / Task
Tokens generated per task
32K28K
Reasoning Tokens / Task
Thinking tokens burned per task
14K11K

Specifiche Tecniche

Architecture, release timeline, capabilities, and modalities.

FeatureQwen3.7 MaxQwen3.6 Max Preview
Official API Model ID (SDK)qwen3-7-max-instructqwen3-6-max-preview-instruct
API ProtocolAlibaba REST API (OpenAI-Compatible)Alibaba REST API (OpenAI-Compatible)
Release Date2026-052026-04
Knowledge CutoffApril 2026March 2026
ArchitectureNext-Generation Deep Frontier Reasoning TransformerHigh-Scale Frontier Agentic Transformer
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)5,000 – 15,000 RPM (Production Tier) · 4,000,000 – 10,000,000 TPM5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($1.8/1M in) across full 1000K windowFlat rate ($1.5/1M in) across full 262K window
Prompt Cache Policy & TTLCached input at $0.18/1M tokensCached input at $0.15/1M tokens
Computer Use / GUI AgentAPI / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)
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 toolsSupported via external Tavily/Exa Search & E2B/Docker Sandbox tools
Official Fine-Tuning SupportAPI Prompt Engineering & RAG DistillationAPI Prompt Engineering & RAG Distillation
Multimodal Token BillingText BPE (~4 chars/token)Text BPE (~4 chars/token)
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 ClassificationAlibaba Production Safety & Alignment VerifiedAlibaba Production Safety & Alignment Verified
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
Output Modalitiestexttext

Qwen3.7 Max vs Qwen3.6 Max Preview: Risposte Rapide (FAQ)

Which is more intelligent, Qwen3.7 Max or Qwen3.6 Max Preview?

Qwen3.7 Max is more intelligent. It scores 92 compared with 90 on the composite Intelligence Index.

Which model is faster?

Qwen3.7 Max is faster, generating 80 tokens per second compared with 75 tokens per second.

Which model is cheaper to run?

Qwen3.6 Max Preview is cheaper at $1.01 per 1M tokens blended, compared with $1.21 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Qwen3.6 Max Preview has lower latency, with a time to first token of 0.54s compared with 0.58s.

Which model has a larger context window?

Qwen3.7 Max has a larger context window, supporting 1M tokens compared with 262.1K tokens.

Verdetto

Sia Qwen3.7 Max (Ideale per i workflow agentici autonomi, il tool calling e l’automazione multi-step, sistemi RAG aziendali e integrazioni API scalabili.) sia Qwen3.6 Max Preview (Ideale per il ragionamento aziendale di frontiera, la programmazione avanzata e i carichi di produzione, sistemi RAG aziendali e integrazioni API scalabili.) eccellono in produzione: Qwen3.7 Max guida nei benchmark di ragionamento e programmazione, Qwen3.7 Max garantisce una generazione più rapida e Qwen3.6 Max Preview offre il miglior rapporto qualità-prezzo per carichi API elevati.

Domande Frequenti (FAQ)

Quale modello è migliore per coding e ragionamento, Qwen3.7 Max o Qwen3.6 Max Preview?+

Nell’indice di intelligenza composito e nei benchmark di programmazione prevale Qwen3.7 Max. Consulta i punteggi SWE-bench e GPQA qui sopra per tutti i dettagli.

Qual è la differenza di prezzo API tra Qwen3.7 Max e Qwen3.6 Max Preview?+

Qwen3.7 Max costa $1.80 / $7.20 per milione di token di input/output, mentre Qwen3.6 Max Preview costa $1.50 / $6.00. Nel costo combinato, Qwen3.6 Max Preview risulta più economico.

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

Qwen3.7 Max supporta 1M token di contesto contro 262.1K token di Qwen3.6 Max Preview, mentre Qwen3.7 Max 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.

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: Documentazione API ufficiale di Alibaba e Alibaba, schede di sistema e benchmark indipendenti (2026).