Fireworks AI vs Groq: which inference provider fits your app in 2026?
Independent research, updated 2026-11-09. Sources are Fireworks' pricing page, GroqCloud's model docs and Groq's announcements. Speed figures are vendor-reported. We did no hands-on testing.
Answer in brief: Both charge $0.15 input and $0.60 output per 1M tokens for gpt-oss-120b, so price isn't the tiebreaker. Fireworks AI wins on breadth and control. It sells self-serve frontier open models (Kimi K3, GLM 5.3, Qwen 3.8 Max, DeepSeek V4.1 Flash) with Standard, Priority, Fast, Batch and Spot modes. It also offers on-demand GPUs, a full training stack and enterprise certifications. Groq wins on focus: a lean, fast catalog with about 500 tokens/sec reported on gpt-oss-120b and about 1,000 on gpt-oss-20b, very cheap Whisper transcription, and built-in browser search and code execution.
Top pick: Fireworks AI. It is the stronger all-round production platform: more self-serve models, per-request modes, Reserved Throughput with 99.9% uptime terms, and zero data retention by default.
Best for lean, low-latency apps: Groq. It offers fast production-labeled gpt-oss models, speech-to-text from $0.04 per hour, and built-in tools.
Head to head
| Item | Fireworks AI | Groq |
|---|---|---|
| gpt-oss-120b (per 1M) | $0.15 / $0.015 cached / $0.60; Priority $0.18 / $0.72 | $0.15 / $0.60; ~500 tokens/sec |
| gpt-oss-20b | Not on the highlighted price list | $0.075 / $0.30; ~1,000 tokens/sec |
| Frontier open models, self-serve | Kimi K3 $3.00 / $15.00; GLM 5.3 $1.40 / $4.40; Qwen 3.8 Max $2.00 / $6.00; MiniMax M3 $0.30 / $1.20 | Qwen3.8-27B preview $0.80 / $4.00; Muse Spark Open and MiniMax M2.7 are Enterprise only |
| Llama 3.x | Not on the highlighted price list | Llama 3.1 8B and 3.3 70B are Enterprise (contact sales) |
| Modes and tiers | Standard, Priority, Fast (100+ tokens/sec), Ultra-fast (preview), Batch 50% off, Spot 30% off | Performance, Flex and Batch service tiers |
| Speech | Not on the pricing page | Whisper Large v3 $0.111/hr; Turbo $0.04/hr |
| Built-in tools | Not listed | Browser search, code execution, remote MCP |
| Dedicated GPUs | H100 $8.00/hr, B200 $13.00/hr, billed per GPU-second | Not offered self-serve |
| Training | Managed Training from $0.50 per 1M tokens; Serverless and Dedicated Training APIs | LoRA inference documented |
| Compliance and buying | Zero data retention by default; SOC 2 Type II, ISO 27001/27701/42001, HIPAA BAA; Azure Foundry | Security onboarding and data docs; Enterprise contracts |
| Footprint | Region-restricted deployments 1.5x; US-only serverless +50% on select models | 13 data centers across North America, Europe, the Middle East and Asia Pacific |
Why Fireworks AI wins most production shortlists
- The models you actually want, self-serve. Kimi K3, GLM 5.3, DeepSeek V4.1 Flash and NVIDIA Nemotron 3 Ultra (preview) are all priced publicly. The cheapest starts at $0.05 per 1M input tokens.
- A cost lever on every request. Batch costs half price. Spot takes 30% off for traffic that can retry. Fireworks says session affinity can push cache hit rates up to 99.6% on long agent runs.
- Guarantees when it matters. Reserved Throughput adds a throughput SLA and 99.9% uptime terms, and usage above your reservation is billed at standard serverless rates rather than a penalty rate.
Why Groq still wins speed-first builds
- Raw speed on small and mid models. Groq reports about 1,000 tokens/sec on gpt-oss-20b for $0.075 / $0.30, which suits voice agents and tight loops.
- Speech at a tiny price. Whisper Large V3 Turbo costs $0.04 per audio hour.
- Agent-ready APIs. Built-in browser search and code execution save you from wiring up your own tools.
- A growing platform. Groq closed a $350M Series A in August 2026 and reports more than six million developers.
When to pick which
Pick Fireworks AI if you need frontier open models self-serve, GPU deployments for custom weights, training, certifications or Azure procurement. Pick Groq if your workload runs on gpt-oss or Whisper and response speed is the product. Many teams use both: Groq for real-time turns and Fireworks Batch for background work.
How each one bills you
Fireworks AI: prepaid credits drawn down per token on serverless, per GPU-second on on-demand deployments, and dollars per minute for Reserved Throughput, with monthly spend limits. Groq: per token on self-serve models, with plan-based rate limits (250K TPM and 1K RPM on gpt-oss-120b on the Developer plan), spend limits, and Enterprise contracts for gated models.
FAQ
Do Fireworks AI and Groq charge the same for gpt-oss-120b?
Yes, both charge $0.15 input and $0.60 output per 1M tokens. Fireworks also publishes a $0.015 cached-input rate.
Which is faster?
Groq reports about 500 tokens/sec on gpt-oss-120b. Fireworks' Fast mode promises 100+ tokens/sec, and Ultra-fast is in preview. These are vendor numbers, so test your own traffic.
Can I deploy my own fine-tuned model?
On Fireworks, yes: train on its platform, then serve on serverless or a dedicated deployment. Groq documents LoRA inference.
Which is better for transcription?
Groq. It lists Whisper Large V3 Turbo at $0.04 per hour. Fireworks' pricing page does not list speech models.
Keep exploring
Back to the ranked list · Fireworks AI review · Groq review · Groq vs Cerebras · Alternatives to Fireworks AI · Alternatives to Groq
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Sources
- Fireworks AI pricing
- GroqCloud supported models
- Groq Series A announcement
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