You are choosing between two OpenAI-compatible inference hosts for the same open models. The decision comes down to one trade: DeepInfra is cheaper on every model both publish, and Fireworks adds managed fine-tuning, HIPAA, and a higher published request ceiling at a 25-33% per-token premium.
On DeepSeek V4 Pro, DeepInfra charges $1.30/M input and $2.60/M output. Fireworks charges $1.74 and $3.48. On Kimi K2.6, DeepInfra is $0.75/$3.50 against Fireworks $0.95/$4.00. On GLM-5.1, $1.05/$3.50 against $1.40/$4.40. The dedicated-GPU gap is wider still: DeepInfra rents an H100 80GB at $1.79/hr; Fireworks charges $7.00/hr on-demand.
All prices below are list prices as of June 2026, sourced from each provider's pricing and docs pages.
- Pick DeepInfra if cost is the priority. It undercuts Fireworks on every shared model (DeepSeek V4 Pro $1.30/$2.60, Kimi K2.6 $0.75/$3.50, GLM-5.1 $1.05/$3.50 per M in/out) and rents a dedicated H100 at $1.79/hr, A100 at $0.89/hr. SOC 2 and ISO 27001, zero-retention, 200 concurrent requests, no free tier.
- Pick Fireworks AI if you need managed fine-tuning (LoRA, DPO, reinforcement fine-tuning priced per training token), HIPAA plus SOC 2 Type II, a published 6,000 RPM ceiling, and a 50% batch-inference discount. You pay 25-33% more per token for it.
Who Wins Per Workload
The answer splits by what you serve and what you need around the tokens.
| Workload / decision | Fireworks AI | DeepInfra |
|---|---|---|
| Cheapest per token (every shared model) | 25-33% pricier | Winner |
| Cheapest dedicated GPU | $7.00/hr H100 | Winner ($1.79/hr H100) |
| Managed fine-tuning in one place | Winner (LoRA/DPO/RFT) | Bring your own checkpoint |
| HIPAA compliance | Winner (HIPAA + SOC 2 II) | SOC 2 + ISO 27001, GDPR/HIPAA measures |
| Highest published request ceiling | Winner (6,000 RPM) | 200 concurrent requests |
| Batch / offline jobs | Winner (50% of serverless) | Not advertised |
| Anthropic models alongside open models | Not offered | Winner (resells Claude) |
| Free credits to start | Winner ($1 free) | No free tier |
Per-Model Token Pricing: DeepInfra Wins Every Row
Both hosts serve the same open weights. DeepInfra is cheaper on every model they both publish, on both input and output. The gap on DeepSeek V4 Pro output alone is $0.88/M.
| Model | Fireworks AI | DeepInfra |
|---|---|---|
| DeepSeek V4 Pro | $1.74 / $3.48 | $1.30 / $2.60 |
| DeepSeek V4 Flash | $0.14 / $0.28 | $0.10 / $0.20 |
| Kimi K2.6 | $0.95 / $4.00 | $0.75 / $3.50 |
| GLM-5.1 | $1.40 / $4.40 | $1.05 / $3.50 |
| GPT-OSS 120B | $0.15 / $0.60 | Not published |
| Cached input discount | 50% (e.g. V4 Pro $0.145) | Per model (e.g. V4 Pro $0.10) |
DeepInfra also resells Anthropic models that Fireworks does not host: Claude Haiku 4.5 at $1.00/$5.00, Sonnet 4.6 at $3.00/$15.00, and Opus 4.8 at $5.00/$25.00 per M in/out. If you want open models and Claude behind one API key, DeepInfra is the single-vendor option.
On DeepSeek V4 Pro, Fireworks output is $3.48/M against DeepInfra $2.60/M, a 34% premium. On Kimi K2.6, Fireworks output is $4.00 against $3.50, a 14% premium. The premium buys managed training, HIPAA, and the higher RPM ceiling, not cheaper tokens.
Dedicated GPU Pricing: Roughly a 4x Gap
This is the most lopsided comparison on the page. DeepInfra's dedicated GPU rates are about a quarter of Fireworks' on-demand rates.
| GPU | Fireworks AI (on-demand) | DeepInfra (dedicated) |
|---|---|---|
| A100 80GB | Not published | $0.89 |
| H100 80GB | $7.00 | $1.79 |
| H200 141GB | $7.00 | $2.19 |
| B200 180GB | $10.00 | $2.79 |
| B300 | $12.00 (288GB) | $4.20 (270GB) |
DeepInfra rents an H100 80GB at $1.79/hr against Fireworks at $7.00/hr, and a B200 at $2.79 against $10.00. For steady self-hosting of a fine-tuned checkpoint, DeepInfra is the obvious cost choice. Fireworks publishes the full Blackwell ladder (B200 and B300) for on-demand bursts where you want the newest hardware without a contract.
Neither host is built for the coding-agent apply loop. If applying model-generated code edits is your bottleneck, that is a different tool (Morph Fast Apply, ~10,500 tok/s, with published benchmarks).
Cost on a Real Workload
- DeepInfra serverless: 50M x $2.60/M output = $130/day = ~$3,900/mo (plus input).
- Fireworks serverless: 50M x $3.48/M output = $174/day = ~$5,220/mo (plus input).
- Difference: ~$1,320/mo on output alone, before counting the input-token gap ($1.30 vs $1.74 per M).
Same model, same API shape. DeepInfra is ~25% cheaper at this volume. If you also need managed fine-tuning, HIPAA, or a guaranteed 6,000 RPM ceiling, Fireworks earns the premium; if you only need tokens, DeepInfra is the cheaper host.
Rate Limits & Billing
The two providers gate throughput differently. Fireworks publishes a hard RPM ceiling and budget tiers; DeepInfra runs a concurrency cap and invoices as you cross spend thresholds.
| Dimension | Fireworks AI | DeepInfra |
|---|---|---|
| Without payment method | 10 RPM | No free tier |
| With payment method | 6,000 RPM fixed ceiling | 200 concurrent requests |
| Budget gating | Tiers: $50 / $500 / $5,000 / $50,000 per mo | Invoices at $20 / $100 / $500 / $2,000 / $10,000 |
| Free credits | $1 for new accounts | None |
| Batch inference | 50% of serverless | Not advertised |
Fireworks tiers raise your monthly budget as you spend more or add a card: Tier 1 ($50/mo) needs a valid card, Tier 2 ($500/mo) needs $50 spent or added, up to Tier 4 ($50,000/mo). DeepInfra is postpaid: you accrue usage and get monthly invoices plus mid-month invoicing each time you cross a usage threshold.
Fine-Tuning: Fireworks Is the Full Platform
Fireworks runs managed training; DeepInfra serves what you bring. This is the clearest capability split between them.
| Model size | LoRA SFT | Full SFT |
|---|---|---|
| Up to 16B | $0.50 | $1.00 |
| 16.1B - 80B | $3.00 | $6.00 |
| 80B - 300B | $6.00 | $12.00 |
| Over 300B | $10.00 | $20.00 |
DPO training costs 2x the SFT rate at each size. After training, you serve the adapter on Fireworks serverless or dedicated infrastructure. DeepInfra does not run managed training at all; its play is letting you deploy your own custom or fine-tuned checkpoint on a dedicated GPU at $0.89 to $4.20/hr. If you want the training and the serving in one platform, Fireworks does both; if you already have a checkpoint and want the cheapest place to serve it, DeepInfra fits.
Feature Surface
Both expose the same OpenAI-compatible API surface. The differences are around it: fine-tuning, batch, Anthropic resale, and free credits.
| Feature | Fireworks AI | DeepInfra |
|---|---|---|
| OpenAI-compatible API | Yes | Yes |
| Structured outputs / tool calling | Yes | Yes |
| Managed fine-tuning | LoRA / DPO / RFT, per-token | Deploy your own |
| Batch inference API | Yes (50% of serverless) | Not advertised |
| Embeddings | $0.008/M (Qwen3 8B $0.10/M) | Yes |
| Resells Anthropic (Claude) | No | Yes (Haiku/Sonnet/Opus) |
| Dedicated GPU rental | On-demand, H100-B300 | Dedicated, A100-B300 |
Fireworks adds a 50% batch-inference discount for non-interactive jobs and per-token managed training. DeepInfra adds Anthropic models alongside open weights, so one DeepInfra key reaches open models and Claude. For embeddings, Fireworks charges $0.008/M for models up to 150M params and $0.10/M for Qwen3 8B embeddings.
Compliance & Data Retention
Both run zero-retention inference by default. They differ on the certification set and on one Google-model caveat.
| Dimension | Fireworks AI | DeepInfra |
|---|---|---|
| SOC 2 Type II | Yes | Yes |
| HIPAA | Yes | Technical/organizational measures |
| ISO 27001 | Not stated | Yes |
| Prompt logging by default | None (open models, opt-in only) | None (deleted after short window) |
| Encryption | TLS 1.2+ in transit, AES-256 at rest | Not detailed on trust page |
Fireworks is SOC 2 Type II and HIPAA compliant, with a Zero Data Retention policy that does not log or store prompts or generations for open models without explicit opt-in, TLS 1.2+ in transit, and AES-256 at rest. DeepInfra is SOC 2 and ISO 27001 certified with stated GDPR and HIPAA measures, deletes prompts and completions from disk and memory after a short retention period, and logs only metadata (request ID, cost, sampling parameters). DeepInfra's one exception is Google models, where Google logs prompts and responses for abuse detection.
When to Use Fireworks AI
- You need managed fine-tuning. LoRA SFT from $0.50/M training tokens (up to 16B) to $10.00/M (over 300B), plus DPO and reinforcement fine-tuning, served on the same platform.
- HIPAA is a hard requirement. SOC 2 Type II plus HIPAA out of the box for healthcare and regulated workloads.
- You need a guaranteed request ceiling. 6,000 RPM with a card on file, with budget tiers up to $50,000/mo.
- Offline batch jobs. The batch inference API runs at 50% of serverless pricing.
- You want to start free. New accounts get $1 in credits to test before committing.
When to Use DeepInfra
- Cost is the constraint. Cheaper on every shared model: DeepSeek V4 Pro $1.30/$2.60, Kimi K2.6 $0.75/$3.50, GLM-5.1 $1.05/$3.50 per M in/out.
- You self-host a fine-tuned model. Dedicated A100 at $0.89/hr, H100 at $1.79/hr, H200 at $2.19/hr, B200 at $2.79/hr, roughly 4x cheaper than Fireworks on-demand.
- You want open models and Claude on one key. DeepInfra resells Claude Haiku 4.5, Sonnet 4.6, and Opus 4.8 alongside open weights.
- You need ISO 27001. DeepInfra is SOC 2 and ISO 27001 certified.
- Concurrency, not RPM, is your shape. 200 concurrent requests per account, raisable, on postpaid billing with no free-tier friction.
When to Use Morph for DeepSeek and Codegen
Most serverless hosts quantize activations to fp8 to cut cost, which degrades output quality. Morph serves DeepSeek with 16-bit (bf16) activations and does not quantize them, so output matches the reference weights. When DeepSeek output fidelity matters, Morph is the best place to run it.
For coding agents specifically, Morph runs codegen-tuned speculative decoding plus custom low-level inference kernels built for code generation, which makes it the fastest and highest-quality option for codegen. morph-dsv4flash (DeepSeek V4 Flash) is $0.139/M input and $0.278/M output. See Morph Open Source Models and pricing.
Frequently Asked Questions
Is Fireworks AI or DeepInfra cheaper?
DeepInfra is cheaper on every model both publish. DeepSeek V4 Pro is $1.30/$2.60 per M in/out on DeepInfra versus $1.74/$3.48 on Fireworks. Kimi K2.6 is $0.75/$3.50 versus $0.95/$4.00. GLM-5.1 is $1.05/$3.50 versus $1.40/$4.40. On dedicated GPUs the gap is roughly 4x: DeepInfra rents an H100 80GB at $1.79/hr versus Fireworks at $7.00/hr on-demand.
How much does DeepSeek V4 cost on Fireworks vs DeepInfra?
DeepSeek V4 Pro is $1.30/M input and $2.60/M output on DeepInfra ($0.10/M cached input). Fireworks charges $1.74/M input and $3.48/M output ($0.145/M cached). For the Flash variant, DeepInfra is $0.10/$0.20 and Fireworks V4 Flash is $0.14/$0.28 per M in/out.
What does an H100 cost on Fireworks AI vs DeepInfra?
DeepInfra rents a dedicated H100 80GB at $1.79/hr, H200 141GB at $2.19/hr, B200 180GB at $2.79/hr, and A100 80GB at $0.89/hr. Fireworks charges on-demand: H100 80GB and H200 141GB both $7.00/hr, B200 180GB $10.00/hr, B300 288GB $12.00/hr. DeepInfra is roughly 4x cheaper on H100 and B200 hardware.
What are the rate limits on Fireworks AI and DeepInfra?
Fireworks allows 10 RPM without a payment method and a fixed 6,000 RPM ceiling with a card, plus spending tiers that cap monthly budget at $50, $500, $5,000, or $50,000 by spend history. DeepInfra runs 200 concurrent requests per account on postpaid billing with mid-month invoices at usage thresholds of $20, $100, $500, $2,000, and $10,000. DeepInfra has no free tier; Fireworks gives new accounts $1 in credits.
Can I fine-tune models on Fireworks AI and DeepInfra?
Fireworks runs managed fine-tuning priced per million training tokens: LoRA SFT is $0.50 (up to 16B), $3.00 (16-80B), $6.00 (80-300B), and $10.00 (over 300B), with DPO at 2x the SFT rate. DeepInfra does not run managed training; you deploy your own fine-tuned checkpoint on a dedicated GPU at $0.89 to $4.20/hr. Fireworks trains and serves in one place; DeepInfra is the cheaper place to serve a model you already trained.
Are Fireworks AI and DeepInfra OpenAI-compatible, and do they log prompts?
Both expose OpenAI-compatible chat completions, embeddings, streaming, structured outputs, and tool calling, so most clients work by swapping the base URL and key. Both run zero-retention by default: Fireworks does not log or store prompts or generations for open models without explicit opt-in, and DeepInfra deletes prompts and completions from disk and memory after a short window, logging only metadata. DeepInfra's exception is Google models, where Google logs prompts for abuse detection.
Related Comparisons
DeepInfra Is the Price Floor; Fireworks Is the Training Stack
DeepInfra undercuts Fireworks on every shared model and on dedicated GPUs. Fireworks adds managed fine-tuning and HIPAA. If applying model-generated code edits is your bottleneck, that is a separate problem Morph Fast Apply solves at ~10,500 tok/s.