What are the strengths of this model?

First Max-class Qwen model to ship open weights (Qwen3.8-2.4T-A95B), enabling self-hosting at frontier scale 2.4T-parameter MoE with only 95B active per token keeps serving cost low relative to dense frontier models 1M-token native context with multimodal (text, image, video) input Strong agentic coding: 74.2% SWE-bench Verified, 93.0 PaperBench, 86.6 Terminal-Bench 2.1 (vendor-reported)

What are the weaknesses of this model?

Hosted Max API remains proprietary and rate-limited despite the open-weight release Cross-lab benchmark comparisons are directional; some Qwen in-house harnesses are new Datacenter-scale download (~1.6TB class) makes full local deployment impractical for most teams

What are the best use cases?

Long-horizon software engineering: autonomous multi-day repository work and PR generation Enterprise knowledge work: financial research, legal compliance audits, and document analysis Multimodal product and design prototyping from text or visual prompts

AlibabaProprietary

Qwen3.8-Max

Name: Qwen3.8-Max
Author: Alibaba

Compare this model

Qwen3.8-Max is Alibaba's largest and most capable Qwen model to date, a 2.4-trillion-parameter Mixture-of-Experts network that activates just 95B parameters per token. Released August 3, 2026 with open weights (Qwen3.8-2.4T-A95B) following on August 12, it pairs a 1M-token context window with native multimodal input (text, image, video) and $2/$6 per-million-token pricing on QwenCloud. It targets long-horizon agentic coding, autonomous research, and end-to-end product build-out, scoring 74.2% on SWE-bench Verified and 93.0 on PaperBench in Alibaba's evaluations.

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Parameters

2.4T (95B active)

Context Window

License

Proprietary

Release Date

2026-08-12

Benchmark Performance

AA Intelligence Index

—

LMArena Elo

—

HLE

—

ARC-AGI-2

—

SWE-bench Verified

74.2

GPQA Diamond

92.6

MMLU-Pro

88.6

LiveCodeBench

—

AIME 2025

—

MATH-500

93.5

API Pricing

Input Price (per 1M tokens)

Output Price (per 1M tokens)

Billing Mode: standard

Strengths

•First Max-class Qwen model to ship open weights (Qwen3.8-2.4T-A95B), enabling self-hosting at frontier scale
•2.4T-parameter MoE with only 95B active per token keeps serving cost low relative to dense frontier models
•1M-token native context with multimodal (text, image, video) input
•Strong agentic coding: 74.2% SWE-bench Verified, 93.0 PaperBench, 86.6 Terminal-Bench 2.1 (vendor-reported)

Weaknesses

•Hosted Max API remains proprietary and rate-limited despite the open-weight release
•Cross-lab benchmark comparisons are directional; some Qwen in-house harnesses are new
•Datacenter-scale download (~1.6TB class) makes full local deployment impractical for most teams

Use Cases

•Long-horizon software engineering: autonomous multi-day repository work and PR generation
•Enterprise knowledge work: financial research, legal compliance audits, and document analysis
•Multimodal product and design prototyping from text or visual prompts

Deep Analysis

Parameters

2.4T (95B active)

MoE, 512 experts, 10 routed + 1 shared per token

Context Window

1M tokens

262,144 native, extensible to 1,010,000

Input / Output Price

$2 / $6 per 1M

QwenCloud; cached input $0.25/M

SWE-bench Verified

74.2%

Vendor-reported; vs Fable 5 76.8%

Release

Aug 3, 2026 (open weights Aug 12)

First Max-class Qwen open weights

Strengths

・First Max-class Qwen model to ship open weights (Qwen3.8-2.4T-A95B), enabling self-hosting at frontier scale
・2.4T-parameter MoE activates only 95B per token, keeping serving cost low relative to dense frontier models
・1M-token native context with multimodal (text, image, video) input
・Strong agentic coding: 74.2% SWE-bench Verified, 93.0 PaperBench, 86.6 Terminal-Bench 2.1 (vendor-reported)

Weaknesses

・Hosted Max API remains proprietary and rate-limited despite the open-weight release
・Cross-lab benchmark comparisons are directional; some Qwen in-house harnesses are new
・Datacenter-scale download (~1.6TB class) makes full local deployment impractical for most teams

Competitor Comparison

Model	Price
Claude Fable 5 (max)	$10/$50
GPT-5.6 Sol (max)	$5/$30
Kimi K3	$3/$15

Overview

Qwen3.8-Max is Alibaba's largest and most capable Qwen model, a 2.4-trillion-parameter MoE that activates 95B parameters per token. Released August 3, 2026 with open weights following on August 12, it offers a 1M-token context, native multimodal input, and $2/$6 per-million-token pricing, targeting long-horizon agentic coding and autonomous research.

Benchmarks & Performance

In Alibaba's evaluations Qwen3.8-Max scores 74.2% on SWE-bench Verified, 88.6% on MMLU-Pro, 92.6% on GPQA Diamond, 67.7% on SWE-bench Pro, and 86.6% on Terminal-Bench 2.1. It reached #2 globally behind Claude Fable 5 on internal leaderboards and #4 on the Frontend Code Arena in third-party testing, trailing Fable 5 on FrontierSWE while leading on several agentic and multimodal surfaces.

Detailed Comparison

Against Claude Fable 5, Qwen3.8-Max closes much of the gap on agentic code refactoring and autonomous tool use while costing a fraction. Against Kimi K3 it leads on most published benchmarks. Against GPT-5.6 Sol it is competitive on agentic and multimodal tasks at far lower price.

Community Feedback

The open-weight release drew strong interest on r/singularity and developer forums, with users noting it lowers the barrier to self-hosted frontier-class AI. The 27B dense variant (Qwen3.8-27B) was welcomed as a practical on-prem option. Some cautioned that the multimodal comparison table was benchmarked against Qwen3.7-Plus rather than Max.

Use Cases

Qwen3.8-Max is designed for multi-day autonomous work: Alibaba reported it operating independently in a live GitHub repo for 10 days (265 commits, 127 PRs) and running 6,000+ backtests for factor research. It suits long-horizon software engineering, enterprise knowledge work (legal compliance, financial research), and multimodal product prototyping from text or visual prompts.

Latest News

On August 12, 2026 Alibaba released the open weights for Qwen3.8 (Qwen3.8-2.4T-A95B), the first Max-class Qwen model to be open-sourced, alongside the 27B dense variant. The hosted Qwen3.8-Max API had launched August 3 at $2/$6 per million tokens with 1M context and native multimodality.

Sources

Analysis generated: 2026-08-13