vs
Groq vs Mistral AI
Groq serves a few open models very fast on its own LPU. Mistral builds a broader family of its own, with 256K context, cloud listings and weights to self-host.
By The Subconscious Team · Updated
Groq vs Mistral AI: key differences
Groq publishes 1,000 tokens per second on GPT-OSS 20B and 500 on GPT-OSS 120B, with tail latency that stays close to the median. That speed comes on a small catalog centered on GPT-OSS and Qwen 3.6 27B, capped around 131K context, after Llama 3.3 70B and Llama 3.1 8B shut down on August 16, 2026. Mistral's pitch is range rather than speed. Its own models all carry 256K context: Medium 3.5 for coding and reasoning at $1.50 in and $7.50 out, Large 3 at $0.50 in and $1.50 out, Small 4 at $0.15 in and $0.60 out, and Codestral for code completion at $0.30 in and $0.90 out.
Groq hosts Whisper for speech to text and Groq Compound, an agentic system with built-in search and code execution, which pairs well with voice agents. Mistral has its own Voxtral speech models, OCR and an Agents API with built-in tools. Deployment is where Mistral pulls away. Groq runs only on GroqCloud and hosts no fine-tuned models, and its long-term investment is an open question since NVIDIA licensed the LPU and hired most of its staff. Mistral runs on its API, Azure, Bedrock, Vertex AI, Snowflake Cortex and watsonx, self-hosts on four GPUs, and offers EU or US regions. Custom training is available through Mistral's enterprise Forge system.
What Groq and Mistral AI do
Groq
Groq serves open models on its own chip, the LPU, which keeps model weights in on-chip SRAM and runs a deterministic schedule instead of waiting on GPU memory. Groq publishes 1,000 tokens per second on GPT-OSS 20B and 500 on GPT-OSS 120B. Latency stays tight between median and tail, which matters for strict SLAs. The API is OpenAI-compatible and also hosts Whisper for speech to text plus an agentic system called Groq Compound with built-in search and code execution.
Example models: GPT-OSS 120B, Qwen 3.6 27B
Full Groq profileMistral AI
Mistral AI is a Paris lab that sells its models through La Plateforme, its own API, and releases most of them as open weights. It consolidated the lineup in 2026. Mistral Medium 3.5, released April 28, is a dense 128B model that merges instruction following, reasoning and coding into one set of weights, and it replaced both Devstral 2 and the Magistral reasoning models. It costs $1.50 in and $7.50 out per million tokens and scores 77.6% on SWE-Bench Verified by Mistral's count. Mistral Small 4, a 119B mixture-of-experts model with 6.5B active, costs $0.15 in and $0.60 out. Mistral Large 3, a 675B MoE under Apache 2.0, runs $0.50 in and $1.50 out. All three carry a 256K context window.
Example models: Mistral Medium 3.5, Mistral Small 4
Full Mistral AI profileShould you choose Groq or Mistral AI?
Groq
Choose Groq for
- Voice agents that need near-instant replies
- Tight SLAs judged on tail latency
- Fast multi-call loops on GPT-OSS
Mistral AI
Choose Mistral AI for
- Contexts between 131K and 256K
- Self-hosting or cloud-marketplace deployment
- Coding agents on Medium 3.5
Groq vs Mistral AI at a glance
| Attribute | Groq | Mistral AI |
|---|---|---|
| Model access | Open weights | Open weights, plus closed Codestral |
| Flagship models | GPT-OSS 120B, Qwen 3.6 27B | Mistral Medium 3.5, Small 4, Large 3 |
| Speed | 500–1,000 tok/s | Unknown |
| Price | Near the floor on small models | $0.15–$1.50 in, $0.60–$7.50 out per 1M |
| Customization | No fine-tuned model hosting | Forge (enterprise); fine-tuning API deprecated |
| Deployment | GroqCloud API | API, Azure, Bedrock, Vertex, self-host |
| Long context | Around 131K max | 256K |
Frequently asked questions
What is the difference between Groq and Mistral AI?
Groq serves a few open models very fast on its own LPU. Mistral builds a broader family of its own, with 256K context, cloud listings and weights to self-host.
When should I choose Groq over Mistral AI?
Voice agents that need near-instant replies; Tight SLAs judged on tail latency; Fast multi-call loops on GPT-OSS.
When should I choose Mistral AI over Groq?
Contexts between 131K and 256K; Self-hosting or cloud-marketplace deployment; Coding agents on Medium 3.5.
Is Groq or Mistral AI cheaper?
Groq: Near the floor on small models. Mistral AI: $0.15–$1.50 in, $0.60–$7.50 out per 1M. The cheaper choice depends on the model and workload.
Which has more context, Groq or Mistral AI?
Groq: Around 131K max. Mistral AI: 256K.
Related comparisons
Running long-horizon agents?
If your agents run past 200K tokens, compare both against Subconscious. Our inference stack treats a long-horizon trace as the primary workload, so speed, cost, and accuracy hold up deep into the trace.