Head-to-Head Model Comparison

Qwen3.7 Max vs Qwen3.8 Max Preview

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.

Qwen3.7 MaxProfile

Qwen3.8 Max PreviewProfile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

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

Qwen3.8 Max Preview

Modello Base a Pesi Aperti

Qwen3.8 Max Preview di Alibaba è un modello di IA progettato per il self-hosting su infrastruttura privata, il fine-tuning e la piena sovranità dei dati, con finestra di contesto da 1M, velocità di 60 token/s, indice di intelligenza di 93/1

Intelligence Index93 / 100

Input Token:

$0.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

75.2%

Differenze Chiave a Colpo d’Occhio

Qwen3.8 Max Preview is 1.0x cheaper for API usage (input + output tokens combined).
Qwen3.7 Max is faster at 80 tok/s vs 60 tok/s.
Qwen3.8 Max Preview leads on SWE-bench coding (75.2% vs 73.5%).

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

Feature	Qwen3.7 Max	Qwen3.8 Max Preview
Intelligence Index Composite reasoning & knowledge score (0-100)	92	93
Provider	Alibaba	Alibaba
Input Price Cost per million input tokens	$1.80 / 1M	$0.00 / 1M
Output Price Cost per million output tokens	$7.20 / 1M	$0.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$1.21 / 1M	$0.00 / 1M
Context Window Maximum input + output tokens	1M tokens~1,500 A4 pages of text	1M tokens~1,500 A4 pages of text
Max Output Tokens Per single request	32K	32K
Throughput Speed Tokens generated per second	80 tok/s	60 tok/s
SWE-bench Verified Real-world software engineering	73.5%	75.2%
GPQA Diamond Graduate-level reasoning	78.5%	79.5%
Cached Input Price Prompt caching discount per 1M tokens	$0.18 / 1M	$0.00 / 1M

Chi vince in ogni categoria?

At-a-glance decision framework

Coding

Qwen3.8 Max Preview

+1.7% SWE-bench lead

Cost

Qwen3.8 Max Preview

1.0x cheaper monthly runtime

Speed

Qwen3.7 Max

+33% faster generation

Context

Tied

1M tokens window

Punteggi Benchmark Verificati

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

Qwen3.7 MaxQwen3.8 Max Preview

SWE-bench Verified (Autonomous Coding)

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

73.5%vs75.2%

GPQA Diamond (Doctorate-Level Science & Math)

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

78.5%vs79.5%

MMLU-Pro (Multi-task Language Understanding)

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

88.5%vs89%

LMSYS Chatbot Arena Elo

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

1470ptsvs1485pts

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs77%

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 vs60 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

Qwen3.8 Max Preview0.68s

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

Qwen3.7 Max6.83s

Qwen3.8 Max Preview9.01s

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)

Qwen3.7 Max Monthly API Bill

$9.45 / month

$1.8/1M in · $7.2/1M out

Qwen3.8 Max Preview Monthly API Bill

$0.00 / month

$0/1M in · $0/1M out

Qwen3.8 Max Preview saves approximately $9.45 / month (100%) under this workload.1.0x 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

Qwen3.8 Max Preview · Strengths & Key Advantages

Finestra di contesto da 1M con capacità massima di output fino a 32K token (SWE-bench Verified 75.2% · GPQA Diamond 79.5%)
Throughput elevato di 60 token/secondo con latenza al primo token (TTFT) di soli 680 ms
Pesi aperti (2.4T total (95B MoE)) pronti per il self-hosting locale o su cloud privato tramite vLLM, SGLang o Ollama

Considerations & Trade-offs

Richiede server GPU dedicati con sufficiente memoria VRAM per l’esecuzione locale a piena precisione
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.

Metric	Qwen3.7 Max	Qwen3.8 Max Preview
Cost per Task Estimated USD to finish one task	$0.38	$0.00
Output Tokens / Task Tokens generated per task	32K	35K
Reasoning Tokens / Task Thinking tokens burned per task	14K	15K

Specifiche Tecniche

Architecture, release timeline, capabilities, and modalities.

Feature	Qwen3.7 Max	Qwen3.8 Max Preview
Official API Model ID (SDK)	qwen3-7-max-instruct	qwen3-8-max-preview-instruct
API Protocol	Alibaba REST API (OpenAI-Compatible)	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date	2026-05	2026-07
Knowledge Cutoff	April 2026	April 2026
Architecture	Next-Generation Deep Frontier Reasoning Transformer	Colossus-Scale Open Sparse Mixture-of-Experts
Parameters	Confidential	2.4T total (95B active MoE)
Enterprise Rate Limits (RPM / TPM)	5,000 – 15,000 RPM (Production Tier) · 4,000,000 – 10,000,000 TPM	Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud
Long-Context Tier (>128K/200K)	Flat rate ($1.8/1M in) across full 1000K window	Free across full context window (only KV-cache VRAM scales)
Prompt Cache Policy & TTL	Cached input at $0.18/1M tokens	Automatic prefix KV-caching in vLLM / SGLang (0 cost)
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	Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools
Official Fine-Tuning Support	API Prompt Engineering & RAG Distillation	Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)
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)	BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 1488 GB VRAM (4-bit Quantized) · 5160 GB VRAM (Native BF16)
Safety & Frontier Classification	Alibaba Production Safety & Alignment Verified	Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)
Enterprise Compliance (ZDR/HIPAA/SOC2)	SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier	100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control
Input Modalities	text	text, vision
Output Modalities	text	text

Qwen3.7 Max vs Qwen3.8 Max Preview: Risposte Rapide (FAQ)

Which is more intelligent, Qwen3.7 Max or Qwen3.8 Max Preview?

Qwen3.8 Max Preview is more intelligent. It scores 93 compared with 92 on the composite Intelligence Index.

Which model is faster?

Qwen3.7 Max is faster, generating 80 tokens per second compared with 60 tokens per second.

Which model is cheaper to run?

Qwen3.8 Max Preview is cheaper at $0.00 per 1M tokens blended, compared with $1.21 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Qwen3.7 Max has lower latency, with a time to first token of 0.58s compared with 0.68s.

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 Qwen3.8 Max Preview (Ideale per il self-hosting su infrastruttura privata, il fine-tuning e la piena sovranità dei dati, sistemi RAG aziendali e integrazioni API scalabili.) eccellono in produzione: Qwen3.8 Max Preview guida nei benchmark di ragionamento e programmazione, Qwen3.7 Max garantisce una generazione più rapida e Qwen3.8 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 Qwen3.8 Max Preview?+

Nell’indice di intelligenza composito e nei benchmark di programmazione prevale Qwen3.8 Max Preview. 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 Qwen3.8 Max Preview?+

Qwen3.7 Max costa $1.80 / $7.20 per milione di token di input/output, mentre Qwen3.8 Max Preview costa $0.00 / $0.00. Nel costo combinato, Qwen3.8 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 1M token di Qwen3.8 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.

Tokens & Pricing Context Window AI Benchmarks Reasoning Models Tool Calling Model Context Protocol (MCP)

Qwen3.7 Max vs Qwen3.8 Max Preview

Cambia e Confronta Qualsiasi Modello

Qwen3.7 Max

Qwen3.8 Max Preview

Chi vince in ogni categoria?

Punteggi Benchmark Verificati

Latenza e Tempo di Risposta

Simulatore Interattivo dei Costi Token

Qwen3.7 Max · Strengths & Key Advantages

Considerations & Trade-offs

Qwen3.8 Max Preview · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Specifiche Tecniche

Qwen3.7 Max vs Qwen3.8 Max Preview: Risposte Rapide (FAQ)

Verdetto

Domande Frequenti (FAQ)

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