Luma Labs API
APIFreeDream Machine API for photorealistic video generation.
Capabilities16 decomposed
physics-aware text-to-video generation with natural motion synthesis
Medium confidenceGenerates photorealistic videos from text prompts using Ray3.14 model with built-in physics simulation and natural motion synthesis. The system interprets semantic descriptions of movement, gravity, and object interactions to produce videos with physically plausible motion rather than interpolated frames. Supports multiple output resolutions (540p, 720p, 1080p) and draft mode for faster iteration, with optional HDR variant for enhanced color grading and dynamic range.
Integrates physics-aware motion synthesis into the generation pipeline rather than relying on frame interpolation or optical flow, enabling semantically coherent motion that respects physical laws described in text prompts. Ray3.14 architecture appears to embed physics constraints during diffusion rather than post-processing.
Produces more physically plausible motion than Runway or Pika Labs' interpolation-based approaches, with explicit support for gravity, collision, and object interaction semantics in text prompts.
cinematic camera control with semantic motion specification
Medium confidenceEnables fine-grained control over camera movement through natural language descriptions of cinematography techniques (sweeping panoramas, close-ups, tracking shots, dolly movements). The system parses camera intent from text prompts and synthesizes corresponding camera trajectories and framing during video generation. Works in conjunction with text-to-video generation to produce videos with intentional camera work rather than static or random viewpoints.
Parses cinematographic intent from natural language rather than requiring manual keyframe specification or camera parameter input. The system infers camera trajectory, framing, and movement timing from semantic descriptions of film techniques, embedding this into the generation process.
Offers more intuitive camera control than Runway's limited camera parameters, and more semantic flexibility than tools requiring explicit keyframe or trajectory specification.
credit-based usage billing with tiered subscription plans and per-operation pricing
Medium confidenceImplements a credit-based billing system where each API operation (video generation, image generation, audio generation, utilities) consumes a specific number of credits. Monthly subscription plans (Plus $30, Pro $90, Ultra $300) provide credit allowances with multipliers for Luma Agents (4x for Pro, 15x for Ultra). Per-operation costs range from 1 credit (background removal) to 768 credits (video-to-video 1080p HDR). Free trial credits are provided but amount not specified.
Uses credit-based billing with per-operation costs rather than per-request or per-minute pricing, enabling fine-grained cost control based on operation type and quality tier. Subscription multipliers (4x/15x for Luma Agents) suggest tiered access to advanced features.
More transparent than per-request pricing by showing exact credit cost per operation. Subscription tiers with multipliers provide cost savings for high-volume users, though credit-to-USD conversion rate is not documented.
draft mode for rapid iteration with lower-cost preview generation
Medium confidenceEnables draft mode for video generation operations, consuming 4 credits (vs. 80 for 1080p full quality) for text-to-video and image-to-video, and 12 credits (vs. 192 for 1080p full quality) for video-to-video. Draft mode produces lower-resolution or lower-quality previews suitable for concept validation and iteration before committing to full-resolution renders. Supports all video generation models and modes.
Provides explicit draft mode with 20x cost reduction (4 vs. 80 credits for text-to-video) compared to full-resolution output, enabling rapid iteration without expensive full-quality renders. Draft mode is integrated into all video generation operations.
More cost-efficient than competitors' single-tier pricing by offering explicit draft mode. Enables faster iteration cycles for prompt engineering and concept validation.
hdr video generation with enhanced color grading and dynamic range
Medium confidenceProvides HDR (High Dynamic Range) variants of Ray3.14 video generation for enhanced color grading, dynamic range, and visual fidelity. HDR variants cost 4x more than standard variants (16 credits draft to 320 credits 1080p for text/image-to-video, 48-768 credits for video-to-video). Enables production-quality output with extended color space and luminance range suitable for premium content and cinema workflows.
Offers explicit HDR variant of Ray3.14 with 4x cost premium, enabling developers to choose between standard and HDR output based on quality requirements. HDR is integrated into all video generation modes (text-to-video, image-to-video, video-to-video).
Provides cinema-grade HDR output as optional upgrade, whereas competitors typically offer single quality tier. Cost premium is transparent, enabling informed quality-cost decisions.
multi-resolution video output with 540p/720p/1080p quality tiers
Medium confidenceSupports multiple output resolutions (540p, 720p, 1080p) for video generation with corresponding credit costs (4-80 for text/image-to-video, 12-192 for video-to-video in standard mode). Developers select resolution based on quality requirements and budget. Higher resolutions consume more credits but produce sharper, more detailed output suitable for different distribution channels and display sizes.
Offers explicit multi-resolution tiers (540p/720p/1080p) with transparent credit costs, enabling developers to make informed quality-cost decisions. Resolution selection is integrated into all video generation operations.
More granular resolution control than competitors offering single-tier output. Transparent per-resolution pricing enables cost optimization for different use cases.
credit-based usage tracking and cost estimation
Medium confidenceProvides transparent credit-based pricing model where each operation consumes a specific number of credits based on model, resolution, and duration. The system enables users to estimate costs before generation and track cumulative usage across operations. Credits are purchased through subscription tiers (Plus $30/mo, Pro $90/mo, Ultra $300/mo) or consumed from free trial allocations.
Implements transparent credit-based pricing where costs are predictable and documented per operation (e.g., Ray3.14 1080p = 80 credits), enabling cost-aware API usage and budget planning. Subscription tiers provide monthly credit allocations with 20% discount for annual billing.
Provides transparent per-operation credit costs (unlike competitors with opaque per-API-call pricing), enabling accurate cost estimation and budget planning for large-scale projects.
subscription tier management with usage scaling
Medium confidenceOffers tiered subscription plans (Plus, Pro, Ultra) with increasing monthly credit allocations and feature access. The system maps subscription tier to usage limits and feature availability (e.g., Plus includes commercial use, Pro includes 4x usage with Luma Agents, Ultra includes 15x usage). Enables users to select tier based on projected usage and feature requirements.
Implements tiered subscription model with explicit usage scaling (Pro = 4x, Ultra = 15x) and feature gating (commercial use in Plus+, Luma Agents in Pro+), enabling users to select tier based on both budget and feature requirements. Annual billing provides 20% discount vs. monthly.
Provides transparent tiered pricing with clear feature differentiation (commercial use, Luma Agents access), whereas competitors often use opaque per-API-call pricing without clear tier benefits, enabling easier subscription selection and budget planning.
image-to-video generation with motion synthesis from static frames
Medium confidenceConverts static images into photorealistic videos by synthesizing plausible motion and scene evolution from a single frame. The system analyzes the input image's composition, objects, and context, then generates natural motion and camera movement that extends the scene temporally. Supports the same resolution options (540p-1080p) and draft mode as text-to-video, with physics-aware motion synthesis ensuring coherent object behavior.
Synthesizes motion from image content analysis combined with optional text prompts, rather than using simple interpolation or optical flow. The system understands object semantics and scene context to generate physically plausible motion extensions of the input image.
Produces more semantically coherent motion than Runway's image-to-video by incorporating physics simulation and scene understanding, rather than relying purely on optical flow or frame interpolation.
video-to-video style transfer and editing with motion preservation
Medium confidenceTransforms existing videos by applying style changes, visual effects, or compositional edits while preserving the original motion and temporal coherence. The system analyzes the input video's motion patterns and object trajectories, then applies transformations (style transfer, color grading, object replacement, scene modification) while maintaining frame-to-frame consistency. Supports draft and full-resolution output with optional HDR enhancement.
Preserves motion and temporal coherence during style transfer by analyzing optical flow and object trajectories, then applying transformations in a way that respects the original motion patterns. This prevents the temporal artifacts and flickering common in naive style transfer approaches.
Maintains temporal consistency better than frame-by-frame style transfer tools, and offers more semantic control than simple video filters or color grading adjustments.
multi-model video generation with third-party model integration
Medium confidenceProvides access to multiple video generation models (Ray3.14, Ray2, Kling 2.6, Veo 3, Veo 3.1) through a unified API, allowing developers to choose models based on quality, speed, or cost requirements. Each model has distinct capabilities and pricing; Ray3.14 is the latest flagship with physics-aware motion, while third-party models (Kling, Veo) offer alternative architectures and cost profiles. System abstracts model selection and parameter passing through a single API interface.
Integrates multiple proprietary and third-party video generation models (Ray, Kling, Veo) under a unified API, abstracting model-specific parameters and response formats. Developers specify model choice via API parameter rather than managing separate endpoints or SDKs.
Offers more model diversity than single-model APIs like Runway or Pika, enabling cost-quality optimization and model comparison without switching platforms.
text-to-image generation with character and style reference control
Medium confidenceGenerates photorealistic images from text prompts using Luma Photon model with optional reference images for character consistency and visual style blending. The system supports two reference modes: character reference (maintaining consistent character appearance across variations) and visual reference (blending aesthetic and style from reference images). Offers 1080p and 720p fast variants for speed-quality tradeoff, with 30 credits per generation.
Supports dual reference modes (character consistency and visual style blending) within a single generation call, allowing semantic control over which aspects of reference images influence output. This enables more nuanced control than simple style transfer or character embedding.
Offers more granular reference control than DALL-E or Midjourney's style parameters, with explicit character consistency mode for game asset and animation workflows.
alternative image generation models with quality-speed tradeoffs
Medium confidenceProvides access to multiple image generation models (Uni-1, Seedream, Nano Banana, GPT Image 1.5) with varying quality tiers, speed profiles, and cost structures. Seedream offers 1K/2K/4K quality tiers (1-3 credits), Nano Banana variants provide 23-53 credits per generation, and GPT Image 1.5 supports Low/Medium/High quality (4-60 credits). Developers select models based on quality requirements, latency constraints, and budget.
Offers explicit quality tiers (1K/2K/4K for Seedream) with corresponding credit costs, enabling developers to make informed quality-cost tradeoffs. This is more transparent than single-tier models that hide quality variation behind model selection.
Provides more granular quality-cost control than DALL-E's single-tier approach, and more model diversity than Midjourney's single-model offering.
text-to-speech and audio generation with multiple voice and music models
Medium confidenceGenerates audio content from text or sound effect descriptions using ElevenLabs v3 (text-to-speech), ElevenLabs SFX v2 (sound effects), and ElevenLabs Music v1 (music generation). Pricing is per-character for TTS (21 credits per 1,000 characters) and per-minute for SFX and music (25 and 98 credits respectively). Integrates audio generation into video workflows, with optional audio variants for video models (720p/1080p with audio).
Integrates third-party ElevenLabs audio models into video generation API, enabling end-to-end audio-visual content creation. Video generation models support optional audio variants (720p/1080p with audio), allowing synchronized video and audio generation in single workflow.
Offers integrated audio generation within video API, reducing need for separate audio tools. Per-character TTS pricing is more granular than per-minute alternatives, enabling cost-efficient short-form narration.
image utility operations with background removal, blending, and reframing
Medium confidenceProvides image manipulation utilities: background removal (1 credit per image), image blending (1 credit per image), and image reframing (2 credits per image). These are lightweight operations complementing image and video generation, enabling post-processing workflows. Background removal isolates subjects, blending combines multiple images, and reframing adjusts composition or aspect ratio.
Offers lightweight image utilities (1-2 credits each) as complementary operations to generation, enabling cost-efficient preprocessing and post-processing workflows. These are positioned as utilities rather than full generation models.
Lower cost than full image generation for simple operations like background removal, and integrated within same API as video generation for streamlined workflows.
video utility operations with reframing and temporal editing
Medium confidenceProvides video reframing utility (32 credits per second of video) for adjusting composition, aspect ratio, or temporal properties of existing videos. This is a lightweight post-processing operation complementing video generation, enabling aspect ratio conversion, composition adjustment, or temporal cropping without regenerating entire videos.
Offers video reframing as a standalone utility operation, enabling aspect ratio conversion and composition adjustment without full video regeneration. Pricing is per-second, making it suitable for short-form content but expensive for long-form.
Integrated within same API as video generation, reducing need for separate video processing tools. Per-second pricing is transparent but expensive compared to batch video processing tools.
Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.
Related Artifactssharing capabilities
Artifacts that share capabilities with Luma Labs API, ranked by overlap. Discovered automatically through the match graph.
Kling AI
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Vidu
AI video generation with consistent characters and multi-scene narratives.
Gen-2 by Runway
An AI tool that creates videos from text, images, or clips, blending creativity with...
Best For
- ✓Creative directors and VFX artists building content pipelines
- ✓Product marketing teams creating demo videos without filming
- ✓Game developers previsualization physics-based scenes
- ✓Commercial production studios requiring photorealistic output
- ✓Filmmakers and cinematographers using AI as a preproduction tool
- ✓Content creators building narrative-driven videos without traditional filming
- ✓Advertising agencies producing cinematic commercials at scale
- ✓Game studios generating in-engine cinematics with controlled camera work
Known Limitations
- ⚠No documented maximum prompt length or complexity constraints
- ⚠Generation time not specified — 'hyperfast' is marketing claim without concrete SLA
- ⚠Physics simulation fidelity depends on prompt clarity; ambiguous descriptions may produce unpredictable motion
- ⚠No fine-tuning or custom physics parameters exposed via API
- ⚠Video duration limits not documented
- ⚠Camera control fidelity depends on prompt specificity — vague descriptions may produce generic framing
Requirements
Input / Output
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About
Dream Machine video generation API creating photorealistic videos from text and image prompts with natural motion, physics-aware generation, and cinematic camera control for creative and commercial applications.
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