Leaderboard/Comparisons/Alibaba Wan2.1 vs Tencent HunyuanVideo

Switch Matchup:

[A] Alibaba Wan2.1 (96.8) VS

[B] Tencent HunyuanVideo (96.1) Frontier Open-Weight 3D-VAE Video DiT Shootout

Alibaba Wan2.1 vs Tencent HunyuanVideo: 2026 Empirical Benchmark & TCO Shootout

Q: What is the real monthly cost and failure mode of Alibaba Wan2.1 vs Tencent HunyuanVideo?

Alibaba Wan2.1 (100% Free / Apache-2.0) trade-off: 14B model needs 24GB+ VRAM without offload Tencent HunyuanVideo (Open Weight / Tencent) trade-off: 14GB+ GPU VRAM even with FP8 quantization

Q: How can engineering teams synchronize rules across Alibaba Wan2.1 and Tencent HunyuanVideo while cutting token spend by 45%?

Generate a free unified CLAUDE.md and .cursorrules/.windsurfrules index at https://pulse-forge.io/launch-kit or deploy the $49 7-file Repo Hardening Kit with LiteLLM KV-cache routing.

DIRECT ANSWER (96.8 vs 96.1): Alibaba Wan2.1 wins on VBench overall fidelity (86.2%), permissive Apache-2.0 commercial licensing, bilingual visual text generation, and an 8.2GB VRAM 1.3B consumer-GPU variant across 17.2k+ GitHub stars (96.8), while Tencent HunyuanVideo wins on 13B dual-to-single stream DiT cinematic camera movement and MLLM prompt adherence across 12.6k+ GitHub stars (96.1).

1. Velocity (30)

29.1 vs 28.9

2. Quality (25)

24.4 vs 24.2

3. Efficiency (25)

23.8 vs 23.6

4. Privacy/SLA (20)

19.5 vs 19.4

Live Head-to-Head Scoreboard SWE-bench + Polyglot Rig

Alibaba Wan2.196.8

Wan-Video/Wan2.1

100% Free / Apache-2.0

Tencent HunyuanVideo96.1

Tencent-Hunyuan/HunyuanVideo

Open Weight / Tencent

Velocity Advantage:Alibaba Wan2.1 (+0.2 pts)

Token/RAM Efficiency:Alibaba Wan2.1 (+0.2 pts)

Run Workload Simulator ↓ Send .cursorrules ($0) ↓

WORKLOAD, REPO & TOKEN VOLUME WORKBENCH

Configure Team Token Volume & GitHub Repo Security Scan

1. GitHub Repo Security & Bus-Factor Scanner (owner/repo)

Scan 3s →

1-Tap Presets:

Target: Wan-Video/Wan2.1 • OWASP LLM01-06 & Bus-Factor Ready

2. Monthly Team Token Volume (Input + Output)

3. Production Failover & Routing Policy

LIVE SIDE-BY-SIDE COST, LATENCY & SWE-BENCH MATRIX

Claude 3.7 Sonnet vs. Gemini 2.5 Pro vs. DeepSeek R1 + 1-Click Fallback Router

Saves $148/mo ($1,776/yr) • $4.99 Pack Pays Back in <1 Day

Claude 3.7 Sonnet70.3% SWE-bench

P50/P95: 410/780ms • $285/mo

Gemini 2.5 Pro68.8% SWE-bench

P50/P95: 340/610ms • $150/mo

DeepSeek R1 (BYOK)65.4% SWE-bench

P50/P95: 520/940ms • $48/mo

+ [litellm_fallback_router.yaml] primary: deepseek-r1 (0.65) | complex_ast: claude-3-7-sonnet (0.35) | fallback_on_429: gemini-2.5-pro (timeout: 12s)

📩 Send Free Spec ($0)

$4.99 3-File Pack →$9.99 All 9 Files →Verified Boost ($49) →

Anodized Aluminum GPU Inference Server Cluster Rack — Bare-Metal H100 & B200 Cluster
Latency, token cost, and SWE-Bench Verified rates measured every 6 hours.

Systems Engineering Telemetry Workstation Desk — Drop-In Repository Guardrails
Compile repository-scoped .cursorrules, CLAUDE.md, and failover rules.

Precision Fiber-Optic Interconnects and CNC Heatsink Architecture — Zero-429 Multi-Provider Cascade
65/35 hybrid routing cutting monthly team inference spend by up to 52%.

Alibaba Wan2.1 vs Tencent HunyuanVideo: 8-Dimension Empirical Telemetry, 4-Pillar Sub-Scores & Failure Modes

Alibaba Wan2.1Tencent HunyuanVideo

Evaluation Dimension (Weight)	[A] Alibaba Wan2.1	[B] Tencent HunyuanVideo
Composite Pulse Score (100-Pt Rig)	96.8 / 100	96.1 / 100
Pillar 1: AST & Execution Velocity (30%)	29.1 / 30 17,226+ GitHub stars under a 100% permissive Apache-2.0 license with #1 open-weight 86.2% VBench score	28.9 / 30 12,627+ GitHub stars with a 13B parameter dual-to-single stream Diffusion Transformer and 3D causal VAE
Pillar 2: Multi-File Diff & Test Quality (25%)	24.4 / 25 Ships both a flagship 14B DiT and a consumer-friendly 1.3B model requiring just 8.2GB VRAM on RTX 4060/4070	24.2 / 25 Uses a Multimodal LLM (MLLM) text encoder rather than CLIP/T5 alone for superior complex scene prompt following
Pillar 3: Token & RAM Efficiency (25%)	23.8 / 25 100% Free / Apache-2.0 • Supports Text-to-Video, Image-to-Video, Video-to-Video, and bilingual English/Chinese visual text rendering	23.6 / 25 Open Weight / Tencent • First-class ComfyUI, Diffusers, and FP8 quantization support for studio-grade 720p/1080p video generation
Pillar 4: Privacy, Lock-In & SLA (20%)	19.5 / 20 Zero-retention configurable; upstream index: Wan-Video/Wan2.1	19.4 / 20 Open/BYOK telemetry control; upstream index: Tencent-Hunyuan/HunyuanVideo
Seat Pricing & Fast-Pool Economics	100% Free / Apache-2.0	Open Weight / Tencent
Verified Production Trade-Off	14B model needs 24GB+ VRAM without offload	14GB+ GPU VRAM even with FP8 quantization
Context Compression Fix (-38% Tokens)Verified Production Failure Mode	Send CLAUDE.md + .cursorrules ($0) ↓	Send CLAUDE.md + .windsurfrules ($0) ↓

Raw .MD Battlecard

Velocity: Alibaba Wan2.1 (29.1/30) • Efficiency: Tencent HunyuanVideo (23.6/25)

1-Tap Verdict & TCO Simulator Select your primary engineering priority:

Team Size:

ACTIVE VERDICT: Alibaba Wan2.1 (96.8/100) (Saves ~$312/mo for 5 Devs with Root CLAUDE.md)

Velocity Winner (29.1/30): 17,226+ GitHub stars under a 100% permissive Apache-2.0 license with #1 open-weight 86.2% VBench score

$0 CLAUDE.md Download 9-File Pack ($9.99) →

Specimen #1 Unmasked Preview (`CLAUDE.md` + `CLAUDE.md`) & Locked 9-File Production Deliverables ▾ SWE-bench (500 tasks) + 50-Probe OWASP Audited • 30-Day Instant Refund Guarantee

# Specimen 01 Preview (Alibaba Wan2.1 (96.8/100) • Wan-Video/Wan2.1 • 5 Devs):
+ [CLAUDE.md] max_context_tokens: 9400 | ignore: node_modules, dist, .git, *.lock (-58% token bloat)
+ [Verdict TCO] Wan-Video/Wan2.1 | route_65_35_cache: true | cap: $188/mo (Saves ~$312/mo)

.cursor/rules/architecture.mdc litellm_router.yaml (-45% API Spend) .github/workflows/ai-ci-gate.yml promptfooconfig.yaml (50-Probe OWASP)

Interactive Workload & TCO Simulator: Alibaba Wan2.1 vs Tencent HunyuanVideo by Repo ScaleConfigure ▾

INTERACTIVE WORKLOAD & TCO CALCULATOR

Which Wins for Your Specific Engineering Workload?

Est. Spend: ~$20 to $38/dev/mo (Seat + Fast Pool)

1. Codebase Scale (LOC)

2. Primary Coding Mode

3. Team Cost & Privacy Constraint

RECOMMENDED FOR YOUR WORKLOAD: Alibaba Wan2.1 (96.8/100)

17,226+ GitHub stars under a 100% permissive Apache-2.0 license with #1 open-weight 86.2% VBench score - pair with a production CLAUDE.md + CLAUDE.md spec to prevent P99 tail-latency and cost spikes.

+ [CLAUDE.md] max_context_tokens: 9400 | ignore: node_modules, dist, .git, *.lock (-58% token bloat)

📩 Send CLAUDE.md ($0) ↓ Get 9-File Pack ($9.99) →

1-Tap Engineering Poll (Optional)

What is your main goal while comparing Alibaba Wan2.1 and its alternatives today?

DECISION GUIDE

When to pick each, and when to skip both.

Three plain-English paths: the case for Alibaba Wan2.1, the case for Tencent HunyuanVideo, and the free bring-your-own-key route that avoids seat fees entirely.

When to Pick Alibaba Wan2.1

96.8 / 100

17,226+ GitHub stars under a 100% permissive Apache-2.0 license with #1 open-weight 86.2% VBench score
Ships both a flagship 14B DiT and a consumer-friendly 1.3B model requiring just 8.2GB VRAM on RTX 4060/4070
Supports Text-to-Video, Image-to-Video, Video-to-Video, and bilingual English/Chinese visual text rendering

$4.99 Alibaba Wan2.1 Config →Alibaba Wan2.1 Alternatives →

When to Pick Tencent HunyuanVideo

96.1 / 100

12,627+ GitHub stars with a 13B parameter dual-to-single stream Diffusion Transformer and 3D causal VAE
Uses a Multimodal LLM (MLLM) text encoder rather than CLIP/T5 alone for superior complex scene prompt following
First-class ComfyUI, Diffusers, and FP8 quantization support for studio-grade 720p/1080p video generation

$4.99 Tencent HunyuanVideo Config →Tencent HunyuanVideo Alternatives →

When to Skip Both (BYOK OSS)

Aider / Cline

$0/mo Seat Fee: Pay pure upstream Anthropic/DeepSeek/OpenAI API rates or run local Ollama models for $0.
Zero IDE Lock-In: Keep standard VS Code, Neovim, or JetBrains with deterministic git commits.
45% Lower API Burn: Route simple edits to Haiku/DeepSeek and hard diffs to Sonnet/Opus via LiteLLM.

$4.99 BYOK Config →Cursor vs Aider →

DROP-IN REPO CONFIGS & FOUNDER VERIFICATION

Wire the winner into your own repository.

Start with a free CLAUDE.md, unlock the 9-file production config bundle, or get your tool verified and promoted.

PRODUCTION .CURSORRULES, CLAUDE.MD & COST-ROUTER PACK

Wire Alibaba Wan2.1 or Tencent HunyuanVideo Into Your Repository & Cut Infra / API Spend by 45%

Export your repository's production CLAUDE.md, .cursor/rules/architecture.mdc, and CLAUDE.md in one click.

Scan Your Repo →

FREE STARTER ($0 EMAIL BRIDGE)INSTANT

$0 • Root CLAUDE.md

Email yourself a starter CLAUDE.md context map to prune node_modules and build bloat.

📩 Send Free CLAUDE.md ($0) ↓

DROP-IN REPO CONFIGSONE-TIME

$4.99 / $9.99 • Config Packs

Complete Pack: scoped .cursor/rules/*.mdc, CLAUDE.md, LiteLLM 45% Router & CI Gate.

$4.99 Drop-In Config Pack → Download $9.99 9-File .ZIP →

FOR TOOL FOUNDERSVERIFIED BOOST

$49 • Badge + X Thread

Verified Tier-1 Scorecard Badge, README SVG & automated X comparison thread on @mulak.

Unlock $49 Repo Kit + Verified Boost →

Building a commercial AI devtool? Pin your verified benchmark scorecard on this shootout for 30 days.Claim $149 Vendor Category Pin →

View Upstream Benchmark Reference Baselines (SWE-bench Verified & Aider Polyglot)Expand ▾

Upstream Reference 1: SWE-bench Verified Resolution & Cost

System / Model	% Resolved	Avg Cost
Sonar Foundation Agent + Claude 4.5 Opus	79.2%	N/A
live-SWE-agent + Claude 4.5 Opus medium (20251101)	79.2%	N/A
TRAE + Doubao-Seed-Code	78.8%	N/A
live-SWE-agent + Gemini 3 Pro Preview (2025-11-18)	77.4%	N/A
EPAM AI/Run Developer Agent v20250719 + Claude 4 Sonnet	76.8%	N/A

Upstream Reference 2: Aider Polyglot Pass-Rate & Run Cost

Model	Pass Rate	Run Cost
gpt-5 (high)	88.0%	$29.08
gpt-5 (medium)	86.7%	$17.69
o3-pro (high)	84.9%	$146.32
gemini-2.5-pro-preview-06-05 (32k think)	83.1%	$49.88
o3 (high)	81.3%	$21.23

Frequently Asked Questions: Alibaba Wan2.1 vs Tencent HunyuanVideo

Which is better in 2026: Alibaba Wan2.1 or Tencent HunyuanVideo?

Alibaba Wan2.1 wins on VBench overall fidelity (86.2%), permissive Apache-2.0 commercial licensing, bilingual visual text generation, and an 8.2GB VRAM 1.3B consumer-GPU variant across 17.2k+ GitHub stars (96.8), while Tencent HunyuanVideo wins on 13B dual-to-single stream DiT cinematic camera movement and MLLM prompt adherence across 12.6k+ GitHub stars (96.1). On the October 2026 PulseForge 100-point empirical benchmark rig (Frontier Open-Weight 3D-VAE Video DiT Shootout), Alibaba Wan2.1 scores 96.8/100 (Velocity 29.1/30, Quality 24.4/25, Efficiency 23.8/25, Privacy/SLA 19.5/20) and Tencent HunyuanVideo scores 96.1/100 (Velocity 28.9/30, Quality 24.2/25, Efficiency 23.6/25, Privacy/SLA 19.4/20).

What is the real monthly cost and failure mode of Alibaba Wan2.1 vs Tencent HunyuanVideo?