Veo 3.1 natively generates synchronized audio together with the video when you call the Gemini/Vertex (Veo) endpoints — you control audio via the text prompt (audio cues, dialogue lines, SFX, ambience) and the same generation job returns an MP4 you can download. If you prefer a single unified API that bundles many providers, CometAPI also offers access to Veo 3.1 (you call CometAPI with your Comet key and request veo3.1/veo3.1-pro). The release is positioned as a direct competitor to other media models (for example OpenAI’s Sora 2), with improvements focused on audio realism, narrative control and multi-shot continuity.

What is Veo 3.1? Veo 3.1 is Google’s latest iteration of the Veo family of text-and-image→video models, Compared with prior Veo releases, Veo 3.1 specifically highlights native audio generation — meaning the model produces synchronized dialogue, ambience, sound effects and musical cues as part of the video output rather than requiring a separate text-to-speech or post production step. It also brings new narrative controls (reference images, first-and-last frame transitions, and scene-extension features) aimed at making multi-shot stories more coherent.

Why that matters: audio is how viewers interpret space, emotion, timing and causality. Native audio generation (dialogue that lines up with lip motion, SFX timed to visible events, and background atmospheres that match scene geography) reduces the manual work required to make a clip feel “real” and lets creators iterate faster on story and mood.

Can Veo 3.1 produce audio — and what kinds of audio can it make? How is audio produced inside the model? Veo 3.1 treats audio as an integrated output modality of the video-generation pipeline. Instead of sending video frames to a separate TTS or Foley engine, Veo’s generation process jointly models audio and visual streams so that timing, acoustic cues and visual events are coherent. That joint modeling is what enables things like conversational exchanges, ambient soundscapes, and synchronized SFX to appear naturally aligned with the generated imagery.“richer native audio” and synchronized sound generation as headline improvements in 3.1.

Why the audio capability is a big deal Historically, many text-to-video systems produced silent video and left audio to a later pipeline. Veo 3.1 changes that by producing audio in the same generation pass — which reduces manual mixing effort, enforces tighter lip sync for short lines, and lets prompts control causal sound events (e.g., “a glass shatters as the camera cuts left”). This has significant implications for production speed, iterative design, and creative prototyping.

What kinds of audio can Veo 3.1 create? Dialogue / speech — multi-speaker dialogue with timing that corresponds to lips and actions. Ambient soundscapes — environmental audio (wind, traffic, room tone) that fits scene geography. Sound effects (SFX) — hits, impacts, doors, footsteps, etc., timed to visual events. Music cues — short musical motifs or mood underscoring that match scene pacing. These audio types are generated natively and are guided primarily by prompt content rather than separate audio parameters.

Technical limits and length Out of the box Veo 3.1 is engineered for high-quality short clips (8-second high-quality outputs for some flows), but the model also supports scene extension and generation bridges (first→last frame, extend from the final second) that enable multi-clip sequences lasting tens of seconds up to a minute or more when stitched via Scene Extension.

How to generate audio with Veo 3.1 (direct, via Google Gemini / Vertex) Step 1: Prerequisites Google account with access to the Gemini API / Vertex AI and a valid API key / credentials (Veo 3.1 is in paid preview for many access paths). The Google genai / Gemini client or the REST endpoint set up in your environment (or Vertex client if you prefer cloud console). Step 2: Choose the right model and access Use veo-3.1-generate-preview (or veo-3.1-fast where speed/cost is a priority). These model strings appear in Google's examples for preview access. You need a paid Gemini API / Google AI key (or access via AI Studio / Vertex AI).

Step 3: Python example — Gemini genai client (recommended, copy/paste) This example shows the shape of a programmatic call (Python, google.genai client). It demonstrates providing a text prompt that contains audio instructions.

pip install google-genai (follow official SDK install)

from google import genai from google.genai import types import time

client = genai.Client(api_key="YOUR_GOOGLE_API_KEY")

prompt = """ Scene: Rainy downtown street, night. Neon reflections on wet pavement. Ambience: continuous distant rain and passing cars. SFX: bus brakes and hiss at 2.3s; umbrella snap at 0.6s. Music: subtle synth pad enters at 0.5s (slow attack). Dialogue: ALICE (soft, tired): "I didn't think we'd still be here." BOB (sighing): "Neither did I. Let's go." Visual: medium close-up on ALICE, camera dolly forward. """

operation = client.models.generate_videos( model="veo-3.1-generate-preview", prompt=prompt, config=types.GenerateVideosConfig( duration_seconds=8, aspect_ratio="16:9", resolution="1080p", number_of_videos=1 ), )

Poll until done (SDK returns an operation object you can poll)

while not operation.done(): print("processing...") time.sleep(2) operation = operation.poll() result = operation.response # check SDK docs for exact structure video_url = result.generated_videos[0].video # URL or base64 depending on SDK print("Download result:", video_url)

Notes: The returned file is typically an MP4 that includes the generated audio track. The key element for audio control above is descriptive audio instructions embedded in the prompt. Veo 3.1 responds to natural-language audio directions to generate synchronized audio tracks.

Step 3 — Using reference images and “Ingredients to video” To keep character appearance and acoustic cues consistent, you can pass up to three reference images that Veo uses to preserve visual style and continuity. The same generation call supports reference_images=[...]. This is recommended when you expect consistent voices or habitual sounds for a character (e.g., the creak of a recurring door).

Step 4 — Extending scenes (Scene extension) with audio continuity Veo 3.1 supports “scene extension,” where new clips are generated off the final second of a prior clip to create longer sequences — and audio is extended in a way that preserves continuity (background ambiences, ongoing music, etc.). Use the video=video_to_extend parameter in the generate_videos call.

Pseudocode: extend a previous clip while preserving audio continuity

operation = client.models.generate_videos( model="veo-3.1-generate-preview", prompt="Continue the scene: morning light brightens, seagulls move closer; audio: swell builds into light strings", video=previous_clip_resource, config=types.GenerateVideosConfig(duration_seconds=10), )

Step 5 — First & last frame bridging (with audio) If you want a smooth transition between two frames (for example, morphing a day shot into a dusk shot), provide image=first_frame and last_frame=last_frame and include audio direction in the prompt. Veo will generate the transitional frames plus audio that reflects the visual progression. Veo typically returns a single mixed audio track inside the MP4.

How do you use the audio tools in Veo 3.1 ?

1. What CometAPI does and why use it CometAPI gives you a single, OpenAI-style REST endpoint to access many models (including Google’s Veo). This is useful if you want a single integration point (billing, quotas, SDK parity) and don’t want to manage multiple vendor keys. Comet documents that Veo 3.1 is offered among their video models.

2. Basic flow to call Veo 3.1 through CometAPI Sign up at CometAPI and create an API key. Confirm the exact model identifier in Comet’s catalog ("Veo 3.1"/"veo3.1-pro"). Use CometAPI’s OpenAI-style endpoint (or their SDK) and set the model field to the Veo model name. Comet will route your request to Google on your behalf. Veo3.1 Async Generation, This API is implemented through our self-developed technology with the following limitations: Video duration is fixed at 8 seconds and cannot be customized Please contact technical support if you encounter any issues

Example Request curl -X POST https://api.cometapi.com/v1/videos
-H "Authorization: Bearer $COMETAPI_KEY"
-F "model=veo3.1"
-F "prompt=A whimsical flying elephant soaring over a vibrant candy-colored cityscape"
-F "size=16x9"
-F "input_reference=@first_frame.png"
-F "input_reference=@last_frame.png" What are best practices for audio-aware prompting with Veo 3.1? Prompt design for good audio (what to include) Use structured “audio lanes” in the prompt. Minimal recommended blocks:

Scene: short description (location, lighting, camera) Ambience: e.g. "distant rain, muffled traffic" SFX: "door slam at 1.6s; footsteps L→R starting 0.8s" Music: "soft piano pad, slow attack, enters at 0.5s" Dialogue: ALICE (soft, weary): "I didn't think we'd make it." BOB (pause, then): "We did." Action: camera moves, character actions to sync SFX

Key tips: label lanes, add short time anchors (e.g., at 1.6s), describe emotional delivery & sound character (e.g., “soft reverb, slow attack”), and if you need stereo panning annotate L / R or L→R. Iteration is typical — generate a short clip (4–8s), then extend.

Prompt structure and tone Use structured lanes: label “Ambience:”, “SFX:”, “Music:”, and “Dialogue:” blocks. Generators work better with predictable patterns. Be specific about timing: short temporal anchors (e.g., “sfx: door slam at 1.6s”) help with tight sync. If exact frame-level accuracy is essential, iterate and refine. Describe sound characteristics: instead of “synth”, say “soft pad with slow attack, 80 BPM feel” to nudge musical mood. Visual → audio consistency If you provide a reference image or start frame, mention where the audio should originate (e.g., “Ambience: muffled city from left, closer to camera; car pass should pan L→R”). This yields more plausible stereo cues and perceived source localization.

Iteration workflow Generate a short clip (4–8s) and evaluate audio sync. If you need longer narrative, use Scene Extension to grow the clip while preserving the final second as continuity seed. For character consistency (voice timbre, accent), use reference images and repeat voice descriptors between clips. Consider using brief repeated textual “voice anchor” lines (e.g., “ALICE — soft mid-Atlantic accent”) to keep voice stable. Postproduction notes Veo gives you a starting MP4 with embedded audio. For advanced mixing (multichannel stems, separate dialogue/music stems), you may still need to extract and recompose audio in a DAW — Veo is primarily for integrated single-file generation. Third-party workflows often combine Veo for base generation and DAW edits for distribution-quality mixes.

Example prompts (copy-paste ready) 1 — Natural-sounding ambient + effect + short dialogue Prompt: Wide shot of an empty diner at 6:00 AM. Audio: humming refrigerator, distant traffic, a single coffee cup clink. Soft acoustic guitar underlay. Dialogue (woman, tired): "Morning's never been this quiet." Sync the clink with the camera pan at 2.5s.

2 — Foley-heavy action beat Prompt: Medium close-up of a courier running through a marketplace. Audio: hurried footsteps on cobblestones, cloth brushing, vendors shouting faintly in background. At 0.8s add a metallic jingle from keys. Fast, rhythmic percussive music fades in at 3s.

3 — Cinematic ambience + character voice Prompt: Interior study lit by candlelight. Audio: crackling fireplace, turning pages, soft string quartet in the background. Dialogue (old man): "Some stories carry their own warmth." Keep the string motif subtle and warm.

4— Tight dialog + SFX (short clip, explicit timing) "Prompt: Interior: cluttered bookstore at 7pm. Camera pans right to a man dropping a book. Audio instructions:

• Ambience: quiet bookstore with rain hitting the windows.
• Dialogue: Speaker A (soft): 'Lo siento...' at 1.2s. Speaker B (firm): 'No te preocupes.' at 2.1s.
• SFX: Book thud at 1.15s. Rain intensity increases at 3.5s. Style: intimate, cinematic. Lip sync and SFX must match timings."

5 — Ambience-first scene (mood, less strict SFX) "Prompt: A seaside boardwalk at sunset. Create a dreamy soundscape with gulls, distant music from a radio, and rolling waves. No spoken lines. Prefer a slow, swelling musical bed under the ambience. Style: nostalgic documentary."

6 — Multi-speaker conversation (stagged) "Prompt: Two people in a busy market, speaking in English and occasionally in Japanese — short lines. Tag speakers clearly. Include periodic vendor shouts (market ambience) and a passing motorcycle SFX at 2.4s."

How does Veo 3.1’s audio compare to Sora 2’s audio? Both Veo 3.1 and OpenAI’s Sora 2 support synchronized audio output tied to generated video. They are positioned as flagship media-generation models from their respective vendors and emphasize realistic audio-video coherence. Both publish APIs .

Key differences Model focus & length: Veo 3.1 emphasizes controllability with features like first/last frame, scene extension for longer sequences, and explicit reference-image conditioning to preserve character and audio continuity across multi-shot sequences. Sora 2 is framed as a flagship model that generates video with synced audio; Sora 2 Pro emphasize high fidelity and tuned trade-offs between quality and cost (Sora 2 Pro tier for higher fidelity). Veo 3.1’s explicitly call out scene extension and multi-prompt sequences. Platform integration: Veo 3.1 is integrated across Google’s Gemini ecosystem (Gemini app, Flow, Gemini API, Vertex AI) whereas Sora 2 is presented as OpenAI’s platform model with API endpoints and a Sora app for iOS; pricing and endpoint structures differ (Sora 2 docs show per-second pricing tiers). Choose based on your existing cloud footprint and compliance needs. Fine-grained video controls: Veo 3.1 calls out several specific creative controls (Ingredients to Video, Scene Extension, First/Last Frame) which reduce iteration time for narrative workflows. Sora 2 focuses on synchronized audio and physical accuracy in motion; both provide controls, but their idioms and SDKs differ. Practical implications for audio-heavy projects If you prioritize out-of-the-box high-fidelity single-shot video with synced audio and a simple per-second pricing model → Sora 2 is a strong competitor; test both on your target assets and budgets.

If you need long continuous narrative with consistent audio motifs across shots → Veo 3.1’s Scene Extension and reference-image conditioning make it attractive.