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Mistral AI vs SambaNova
SambaNova sells fast decode on large open models from its own RDU chip. Mistral sells its own model family with wider cloud reach and in-region processing.
By The Subconscious Team · Updated
Mistral AI vs SambaNova: key differences
SambaCloud serves MiniMax M2.7, DeepSeek, Gemma 4 31B and GPT-OSS 120B, the last at $0.22 in and $0.59 out. SambaNova claims its SN50 rack runs MiniMax M2.7 near 820 tokens per second in its fastest configuration, and context reaches 192K on that model. Mistral serves only its own models with 256K context: Small 4 at $0.15 in and $0.60 out prices close to SambaNova's GPT-OSS rate, Large 3 costs $0.50 in and $1.50 out, and Medium 3.5 costs $1.50 in and $7.50 out. SambaNova's RDU hot swaps between models in milliseconds with input caching, which suits agents that bounce between models.
Much of SambaNova's value arrives through hardware sales and partnerships. SN50 ships in the second half of 2026, SambaNova claims 5x the peak speed of an NVIDIA B200, and many headline numbers are vendor benchmarks on hardware still ramping. It also sells racks to neoclouds that want a fast tier without replacing GPUs. Mistral leans on self-serve access instead, with an Agents API, Codestral, OCR and Voxtral, listings on Azure, Bedrock, Vertex AI, Snowflake Cortex and watsonx, EU and US regional endpoints and a Priority Tier with uptime SLAs. Open weights let Medium 3.5 self-host on four GPUs, and custom training runs through Mistral's enterprise Forge.
What Mistral AI and SambaNova do
Mistral 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 profileSambaNova
SambaNova designs its own inference chip, the Reconfigurable Dataflow Unit, and sells fast tokens on large open models through SambaCloud. The RDU maps the model graph onto the chip to cut trips to off-chip memory. A three-tier memory design of SRAM, HBM and bulk DRAM lets one system host very large models and hot swap between several of them in milliseconds. SambaCloud serves models like MiniMax M2.7, DeepSeek, Gemma 4 31B and GPT-OSS 120B, with speeds reported by Artificial Analysis.
Example models: MiniMax M2.7, GPT-OSS 120B
Full SambaNova profileShould you choose Mistral AI or SambaNova?
Mistral AI
Choose Mistral AI for
- Self-serve access to a full model family
- EU data residency
- Self-hosting open weights
SambaNova
Choose SambaNova for
- Fast decode on MiniMax M2.7 and other large open models
- Agents that switch models mid-task
- Neoclouds adding a premium speed tier
Mistral AI vs SambaNova at a glance
| Attribute | Mistral AI | SambaNova |
|---|---|---|
| Model access | Open weights, plus closed Codestral | Open weights |
| Flagship models | Mistral Medium 3.5, Small 4, Large 3 | MiniMax M2.7, GPT-OSS 120B, DeepSeek |
| Speed | Unknown | ~820 tok/s on MiniMax M2.7 (SN50) |
| Price | $0.15–$1.50 in, $0.60–$7.50 out per 1M | $0.22 in, $0.59 out (GPT-OSS 120B) |
| Customization | Forge (enterprise); fine-tuning API deprecated | Unknown |
| Deployment | API, Azure, Bedrock, Vertex, self-host | SambaCloud, racks for neoclouds |
| Long context | 256K | Up to 192K (MiniMax M2.7) |
Frequently asked questions
What is the difference between Mistral AI and SambaNova?
SambaNova sells fast decode on large open models from its own RDU chip. Mistral sells its own model family with wider cloud reach and in-region processing.
When should I choose Mistral AI over SambaNova?
Self-serve access to a full model family; EU data residency; Self-hosting open weights.
When should I choose SambaNova over Mistral AI?
Fast decode on MiniMax M2.7 and other large open models; Agents that switch models mid-task; Neoclouds adding a premium speed tier.
Is Mistral AI or SambaNova cheaper?
Mistral AI: $0.15–$1.50 in, $0.60–$7.50 out per 1M. SambaNova: $0.22 in, $0.59 out (GPT-OSS 120B). The cheaper choice depends on the model and workload.
Which has more context, Mistral AI or SambaNova?
Mistral AI: 256K. SambaNova: Up to 192K (MiniMax M2.7).
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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.