Wan 2.7: Alibaba's New Video Model with First-Frame Control and 15-Second Clips

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Key Takeaway

Wan 2.7 is best for workflows that need precise compositional control — first/last frame anchoring, multi-reference consistency, or post-generation editing without full regeneration. These are capabilities that most other video models at this tier do not offer.

• Use Wan 2.7 if: you need to define exact start and end frames (FLF2V), maintain character consistency across shots using multiple reference videos, or edit generated clips via natural language instruction
• Consider alternatives if: you need native audio in the output (Veo 3.1 Lite or PixVerse V6), parameterized camera controls (PixVerse V6), or confirmed open-source self-hosting today (Wan 2.1/2.6)

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What Can Wan 2.7 Do That Other AI Video Generators Can't?

Wan 2.7 is currently the only major AI video model with first/last frame control (FLF2V) — you set both the opening and closing frame, and the model generates the motion between them. It also accepts up to 5 reference videos simultaneously for character consistency, and supports instruction-based editing of existing clips without full regeneration. Neither capability exists in Veo 3.1 Lite, PixVerse V6, or Kling 3.0.

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What Is Wan 2.7?

Wan 2.7 is the latest video generation model from Alibaba's Tongyi Lab. It was made available in March 2026 via the WaveSpeedAI API (wavespeed.ai) and through Alibaba Cloud's DashScope platform, with an official GitHub release pending.

Wan is Alibaba's flagship open-source video generation family. Wan 2.1 shipped under Apache 2.0 and attracted substantial developer adoption. Wan 2.7 is the most capable version to date, adding a set of professional-grade controls that earlier releases lacked.

The model is built on a Diffusion Transformer + Flow Matching architecture — estimated at around 27 billion parameters. This puts it in the same architectural class as the current generation of high-performing video models, using latent flow matching rather than older DDPM-style diffusion for faster, more stable generation.

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What Changed from Wan 2.6

Wan 2.7 is not a minor patch. Here is the practical feature delta:

The additions are substantial. First/last frame control, multi-reference input, and instruction editing are all professional workflow capabilities that were missing from Wan 2.6.

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Key New Features in Detail

First / Last Frame Control (FLF2V)

FLF2V lets you define both the first and last frame of a video, then have Wan 2.7 generate the motion between them. This is a meaningful control surface for commercial work — you can set a specific starting composition, specify where the shot ends up, and let the model handle the camera and subject movement in between.

Use cases:

• Product shots where you need the item to start centered and end at a specific angle
• Character animations where the pose changes need to be exact at both ends
• Cinematic transitions between two established compositions

Multi-Reference Video Input

Wan 2.7 accepts up to 5 reference videos simultaneously. The model reads them to inform character consistency, environment style, and motion patterns in the generated clip. This is more sophisticated than single-image reference and addresses one of the persistent complaints about video generation: characters that don't hold consistent appearance across shots.

For commercial use, this means you can provide examples of how a product moves, how a person looks, or what environment style you want — and the model applies that context to new generations.

9-Grid Image Input

The 9-grid input accepts a 3×3 arrangement of images as a single input. The model reads all nine frames to understand context, character, or environment from multiple angles. This is particularly useful for character consistency work where a single reference image doesn't capture enough detail.

Instruction-Based Video Editing

Rather than regenerating from scratch, Wan 2.7 accepts natural language instructions to modify an existing video. You can describe what you want changed — background color, lighting mood, subject clothing, or visual style — and the model applies the edit while preserving the original motion.

This reduces the iteration cost significantly for commercial video production, where small adjustments to an approved motion are common.

Multi-Language Lip Sync

Wan 2.7 adds multi-language lip sync support, meaning generated character speech animations can be synchronized with audio in different languages. This is a meaningful feature for localization workflows.

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Technical Specifications

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Known Limitations

No model is perfect. Here is what Wan 2.7 does not do:

• No 4K native output. The maximum resolution is 1080P. If you need 4K for digital signage, cinema pre-viz, or large-screen display, you will need to use a different model or upscale in post.
• Open-source release not confirmed at launch. Wan 2.1 was fully open source under Apache 2.0. Wan 2.7's open-source release status had not been officially announced at the time of writing — check the Alibaba Wan GitHub for the latest.
• No official pricing published. API pricing on WaveSpeedAI and DashScope should be verified at those platforms. The reference point is Wan 2.6 API rates, but Wan 2.7 pricing may differ.
• New model, limited community testing. Wan 2.7 is recent. The wider community testing that exists for older models is still accumulating.

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How to Use Wan 2.7

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Related Reading

• Wan 2.7 vs Wan 2.6 — Full breakdown of what changed between versions
• PixVerse V6 — If you need parameterized camera controls or a multi-shot engine
• Veo 3.1 Lite — If native audio generation is a priority over compositional control

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FAQ

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How Wan 2.7 Compares

Wan 2.7 uniquely offers first/last frame control and instruction-based editing — both absent from the other models in this comparison. If either capability is relevant to your workflow, Wan 2.7 is currently the only option that provides them. For audio-included output, Veo 3.1 Lite and PixVerse V6 are the better choices.

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Try Wan 2.7 Now

→ Generate with Wan 2.7 — text-to-video and image-to-video, no API setup required.

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Disclosure

Model facts and feature descriptions are sourced from Alibaba Tongyi Lab's official release materials for Wan 2.7 (March 2026) and the WaveSpeedAI API documentation. Open-source release status and official pricing were pending confirmation at time of publication — verify both at the official Alibaba Wan GitHub and wavespeed.ai respectively.