Decision comparison
Fireworks AI vs Replicate
For LLM-heavy production workloads, compare token billing, fine-tuning workflow, batch inference options, and service terms using the models you intend to deploy. Replicate wins for multimodal teams needing image, video, and audio generation alongside text, with its community marketplace of 1000+ models and per-second compute billing.
Direct comparison. These are reviewed substitutes bought for the same job, so the differences below are the ones that decide between them.
All 2 are model hosting platforms.
Quick Comparison
| Decision factor | Fireworks AI | Replicate |
|---|---|---|
| Pricing Model | Fireworks AI bills per token for serverless inference, with $1 in free credits for new accounts; per-model rates across its Standard, Priority and Fast serverless tiers are published in its documentation rather than on the pricing page. Embeddings are $0.008 per 1M input tokens up to 150M parameters, $0.016 from 150M to 350M, and $0.1 for Qwen3 8B. Managed training is priced per 1M training tokens, with LoRA SFT at $0.50 for models up to 16B, $3.00 from 16.1B to 80B, $6.00 from 80B to 300B and $10.00 above 300B; DPO and full-parameter tuning are multiples of those. On-demand GPU deployments from 1 September are $8.00 per hour for H100 and H200, $13.00 for B200, $15.00 for B300 and $20.00 for GB300, with a 1.5x premium on region-restricted deployments. | Replicate uses pure pay-as-you-go pricing billed per second of compute. Hardware rates: CPU $0.09/hr, Nvidia T4 $0.81/hr, A100 80GB $5.04/hr, H100 $5.49/hr, 4x H100 $21.96/hr, 8x H100 $43.92/hr. Public models: Flux Schnell $0.003/image, Flux 1.1 Pro $0.04/image, DeepSeek R1 $3.75/1M input tokens. Video: Wan 2.1 480p $0.09/second of video. No subscription required. Enterprise volume discounts via committed spend. |
| Primary Focus | Specialized LLM inference platform optimized for transformer architectures | General-purpose model marketplace for text, image, video, and audio inference |
| Fine-tuning | Integrated LoRA SFT pipeline at $0.50-$10.00/1M training tokens by model size | No native fine-tuning; deploy externally trained models via Cog packaging |
| Model Breadth | Curated set of optimized LLMs from sub-4B to 100B+ MoE architectures | 1000+ community-published models across all generative AI modalities |
| GPU Pricing | Fireworks AI bills per token for serverless inference, with $1 in free credits for new accounts; per-model rates across its Standard, Priority and Fast serverless tiers are published in its documentation rather than on the pricing page. Embeddings are $0.008 per 1M input tokens up to 150M parameters, $0.016 from 150M to 350M, and $0.1 for Qwen3 8B. Managed training is priced per 1M training tokens, with LoRA SFT at $0.50 for models up to 16B, $3.00 from 16.1B to 80B, $6.00 from 80B to 300B and $10.00 above 300B; DPO and full-parameter tuning are multiples of those. On-demand GPU deployments from 1 September are $8.00 per hour for H100 and H200, $13.00 for B200, $15.00 for B300 and $20.00 for GB300, with a 1.5x premium on region-restricted deployments. | Replicate uses pure pay-as-you-go pricing billed per second of compute. Hardware rates: CPU $0.09/hr, Nvidia T4 $0.81/hr, A100 80GB $5.04/hr, H100 $5.49/hr, 4x H100 $21.96/hr, 8x H100 $43.92/hr. Public models: Flux Schnell $0.003/image, Flux 1.1 Pro $0.04/image, DeepSeek R1 $3.75/1M input tokens. Video: Wan 2.1 480p $0.09/second of video. No subscription required. Enterprise volume discounts via committed spend. |
| Multimodal Support | FLUX.1 Kontext Pro; no video or audio models | Flux $0.003-$0.04/image, Wan 2.1 $0.09/sec video, audio models available |
Fireworks AI
- Pricing Model:
- Fireworks AI bills per token for serverless inference, with $1 in free credits for new accounts; per-model rates across its Standard, Priority and Fast serverless tiers are published in its documentation rather than on the pricing page. Embeddings are $0.008 per 1M input tokens up to 150M parameters, $0.016 from 150M to 350M, and $0.1 for Qwen3 8B. Managed training is priced per 1M training tokens, with LoRA SFT at $0.50 for models up to 16B, $3.00 from 16.1B to 80B, $6.00 from 80B to 300B and $10.00 above 300B; DPO and full-parameter tuning are multiples of those. On-demand GPU deployments from 1 September are $8.00 per hour for H100 and H200, $13.00 for B200, $15.00 for B300 and $20.00 for GB300, with a 1.5x premium on region-restricted deployments.
- Primary Focus:
- Specialized LLM inference platform optimized for transformer architectures
- Fine-tuning:
- Integrated LoRA SFT pipeline at $0.50-$10.00/1M training tokens by model size
- Model Breadth:
- Curated set of optimized LLMs from sub-4B to 100B+ MoE architectures
- GPU Pricing:
- Fireworks AI bills per token for serverless inference, with $1 in free credits for new accounts; per-model rates across its Standard, Priority and Fast serverless tiers are published in its documentation rather than on the pricing page. Embeddings are $0.008 per 1M input tokens up to 150M parameters, $0.016 from 150M to 350M, and $0.1 for Qwen3 8B. Managed training is priced per 1M training tokens, with LoRA SFT at $0.50 for models up to 16B, $3.00 from 16.1B to 80B, $6.00 from 80B to 300B and $10.00 above 300B; DPO and full-parameter tuning are multiples of those. On-demand GPU deployments from 1 September are $8.00 per hour for H100 and H200, $13.00 for B200, $15.00 for B300 and $20.00 for GB300, with a 1.5x premium on region-restricted deployments.
- Multimodal Support:
- FLUX.1 Kontext Pro; no video or audio models
Replicate
- Pricing Model:
- Replicate uses pure pay-as-you-go pricing billed per second of compute. Hardware rates: CPU $0.09/hr, Nvidia T4 $0.81/hr, A100 80GB $5.04/hr, H100 $5.49/hr, 4x H100 $21.96/hr, 8x H100 $43.92/hr. Public models: Flux Schnell $0.003/image, Flux 1.1 Pro $0.04/image, DeepSeek R1 $3.75/1M input tokens. Video: Wan 2.1 480p $0.09/second of video. No subscription required. Enterprise volume discounts via committed spend.
- Primary Focus:
- General-purpose model marketplace for text, image, video, and audio inference
- Fine-tuning:
- No native fine-tuning; deploy externally trained models via Cog packaging
- Model Breadth:
- 1000+ community-published models across all generative AI modalities
- GPU Pricing:
- Replicate uses pure pay-as-you-go pricing billed per second of compute. Hardware rates: CPU $0.09/hr, Nvidia T4 $0.81/hr, A100 80GB $5.04/hr, H100 $5.49/hr, 4x H100 $21.96/hr, 8x H100 $43.92/hr. Public models: Flux Schnell $0.003/image, Flux 1.1 Pro $0.04/image, DeepSeek R1 $3.75/1M input tokens. Video: Wan 2.1 480p $0.09/second of video. No subscription required. Enterprise volume discounts via committed spend.
- Multimodal Support:
- Flux $0.003-$0.04/image, Wan 2.1 $0.09/sec video, audio models available
Public signals
Verified factual signals only. Bars appear only for like-for-like metrics with five weekly assessments for every tool; missing evidence stays explicit. These signals do not establish enterprise adoption, product quality, or total cost.
| Metric | Fireworks AI | Replicate |
|---|---|---|
| GitHub commits, 90d(Developer adoption) | 31 | 0 |
| GitHub stars(Developer adoption) | 10 | 598 |
| Search interest(Market interest) | 6 | 1 |
| Hacker News mentions, 90d(Community interest) | 0 | 0 |
| Hugging Face downloads(Product adoption) | 11.4k | Not available |
| Hugging Face likes(Product adoption) | 341 | Not available |
| PyPI weekly downloads(Developer adoption) | 260.8k | 364.9k |
| npm weekly downloads(Developer adoption) | Not available | 397.7k |
As of September 21, 2026 — updated weekly.
Health & risk evidence
Observed public-source checks for mapped package versions and repositories.
Fireworks AI
September 21, 2026Package vulnerabilities
PyPI · fireworks-ai@1.2.14
0 vulnerabilities
across 1 package
Repository security score
Not available
Replicate
September 21, 2026Package vulnerabilities
npm · replicate@1.4.0 · PyPI · replicate@1.0.7
0 vulnerabilities
across 2 packages
Repository security score
Not available
Feature Comparison
| Feature | Fireworks AI | Replicate |
|---|---|---|
| Core Inference | ||
| Pricing Model | Per-token billing scaled by model parameter count | Per-second compute billing tied to GPU hardware tier |
| LLM Serving | Optimized serverless endpoints for transformer models sub-4B to 100B+ MoE | General-purpose inference via community-published model containers |
| Image Generation | FLUX.1 Kontext Pro | Flux Schnell $0.003/image, Flux 1.1 Pro $0.04/image, plus community models |
| Video Generation | Not available as a primary offering | Wan 2.1 at $0.09 per second of video output |
| Audio Models | No native audio model support | Community-published audio models via marketplace |
| Training & Customization | ||
| Fine-tuning | Integrated LoRA SFT at $0.50-$10.00 per million training tokens | No native fine-tuning; deploy externally trained models via Cog |
| Custom Model Deployment | Deploy fine-tuned models on dedicated GPUs or serverless | Package any model with Cog and deploy on any GPU tier |
| Model Marketplace | Curated catalog of optimized LLMs selected for inference performance | Open marketplace with 1000+ community-published models across all modalities |
| Pricing & Infrastructure | ||
| Serverless LLM Cost (sub-4B) | No idle-compute charges | Per-second billing on T4/A100/H100 (cost varies by throughput) |
| Dedicated GPU (H100) | $8.00 per hour for H100 and H200 | multi-GPU up to 8x H100 at $43.92/hr |
| Batch Inference | 50% discount on batch processing jobs | No dedicated batch pricing tier |
| Cached Input Discount | 50% discount on cached/repeated input tokens | No equivalent caching price reduction |
| Free Tier | $1 in free credits for new accounts | Pay-as-you-go with no subscription minimum |
| Enterprise Options | Dedicated GPU deployments with guaranteed capacity | Committed spend agreements with volume discounts |
Core Inference
Pricing Model
LLM Serving
Image Generation
Video Generation
Audio Models
Training & Customization
Fine-tuning
Custom Model Deployment
Model Marketplace
Pricing & Infrastructure
Serverless LLM Cost (sub-4B)
Dedicated GPU (H100)
Batch Inference
Cached Input Discount
Free Tier
Enterprise Options
Which to choose
For LLM-heavy production workloads, compare token billing, fine-tuning workflow, batch inference options, and service terms using the models you intend to deploy. Replicate wins for multimodal teams needing image, video, and audio generation alongside text, with its community marketplace of 1000+ models and per-second compute billing.
Best-fit scenarios
Choose Fireworks AI if:
Choose Fireworks AI for production LLM inference where cost predictability, fine-tuning, and batch processing discounts matter. Token pricing beats per-second billing for high-throughput text workloads.
Choose Replicate if:
Choose Replicate for multimodal applications spanning image ($0.003-$0.04), video ($0.09/sec), and audio generation, or when you need rapid access to the latest open-source models via the community marketplace.
Choose Fireworks AI if:
Choose Fireworks AI when you need integrated fine-tuning (LoRA SFT) and dedicated GPU deployments with guaranteed capacity for latency-sensitive production applications.
These scenarios reflect the available product evidence. Your requirements, existing stack, and team expertise should guide the final decision.
Frequently Asked Questions
Can I fine-tune models on Replicate?
Replicate does not offer native fine-tuning infrastructure comparable to Fireworks AI's LoRA SFT pipeline. To run a fine-tuned model on Replicate, you would train the model externally, package the weights using Cog, and deploy the resulting container to Replicate.
Which platform is cheaper for image generation?
For basic image generation, Replicate is cheaper: Flux Schnell costs $0.003 per image. However, these are different model variants targeting different quality levels. Replicate also offers Flux 1.1 Pro at $0.04/image, matching Fireworks AI's price point for higher-quality output.
How do the GPU hourly rates compare?
Replicate offers H100 GPUs at $5.49 per hour, while Fireworks AI prices H100 at $8.00 per hour. Fireworks AI offers B200 GPUs at $13.00 per hour, which Replicate does not currently list. Replicate provides multi-GPU configurations (4x H100 at $21.96/hr, 8x H100 at $43.92/hr).
Is one platform more suitable for production deployments?
Both platforms support production workloads, but they optimize for different profiles. Fireworks AI's dedicated GPU option is designed for applications needing consistent latency and high throughput. Replicate's autoscaling handles bursty workloads well. For LLM production at scale, Fireworks AI provides more predictable unit economics. For multimodal systems, Replicate's unified API simplifies the operational surface.