Mistral Medium 3 vs NVIDIA Nemotron 3 Ultra

Mistral AI · France  |  NVIDIA · US · Updated June 2026

Quick verdict

Pick Mistral Medium 3 for strong cost-to-capability at $0.40/$2.00 or general reasoning, coding and multimodal tasks. Pick NVIDIA Nemotron 3 Ultra for the most capable open-weight model from a us lab (artificial analysis intelligence index of about 48) or fast, efficient long-horizon agentic reasoning via a hybrid mamba-transformer design. Choose NVIDIA Nemotron 3 Ultra if you need self-hosting or data privacy; Mistral Medium 3 if you want a managed API.

Mistral Medium 3 (Mistral AI, France) and NVIDIA Nemotron 3 Ultra (NVIDIA, US) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. Mistral Medium 3 is mistral's mid-tier model at $0.40/$2.00 — efficient general capability with a 128K window, below the 1M-context frontier tier. NVIDIA Nemotron 3 Ultra is nVIDIA's open-weight reasoning flagship (about 550B total, 55B active) — the most capable open model from a US lab, built for long-running agents. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.

Key differences at a glance

Side-by-side specs

SpecMistral Medium 3NVIDIA Nemotron 3 Ultra
ProviderMistral AI (France) NVIDIA (US)
ReleasedMay 7, 2025 June 4, 2026
Context window128K (~192 pages) 1M (~1,500 pages)
Price (in/out)$0.4/$2 per 1M tokens Open weight (self-host / free)
Open weight?No — API only Yes — self-hostable
Modalitiestext, image, code text, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

Strong cost-to-capability at $0.40/$2.00

Mistral Medium 3

Mistral Medium 3 lists strong cost-to-capability at $0.40/$2.00 among its strengths; NVIDIA Nemotron 3 Ultra does not.

General reasoning, coding and multimodal tasks

Mistral Medium 3

Mistral Medium 3 lists general reasoning, coding and multimodal tasks among its strengths; NVIDIA Nemotron 3 Ultra does not.

Efficient mid-tier deployment for production workloads

Mistral Medium 3

Mistral Medium 3 lists efficient mid-tier deployment for production workloads among its strengths; NVIDIA Nemotron 3 Ultra does not.

The most capable open-weight model from a US lab (Artificial Analysis Intelligence Index of about 48)

NVIDIA Nemotron 3 Ultra

Open weights make this possible at all — Mistral Medium 3 is API-only, so it cannot leave the vendor's servers.

Fast, efficient long-horizon agentic reasoning via a hybrid Mamba-Transformer design

NVIDIA Nemotron 3 Ultra

Its 1M window holds about 7.8× more than Mistral Medium 3's 128K in a single prompt.

A fully open release — weights, training data, and recipes under a permissive license

NVIDIA Nemotron 3 Ultra

Mistral Medium 3 is comparatively weak here — proprietary, unlike Mistral's open-weight releases

Lowest cost at scale

NVIDIA Nemotron 3 Ultra

Its weights are open, so at volume you pay for your own hardware instead of Mistral Medium 3's $0.4/$2 per 1M tokens.

Largest single-prompt input

NVIDIA Nemotron 3 Ultra

Its 1M window is about 7.8× larger than Mistral Medium 3's 128K, fitting roughly 1,500 pages in one prompt.

Which should you pick?

A cost-sensitive startup shipping high volume

NVIDIA Nemotron 3 Ultra

At Open weight (self-host / free) it undercuts Mistral Medium 3, and on millions of tokens that margin decides the monthly bill.

Someone analysing very long documents or codebases

NVIDIA Nemotron 3 Ultra

Larger 1M window fits more in one prompt.

A team with data-privacy or self-hosting needs

NVIDIA Nemotron 3 Ultra

Open weights let you run it on your own hardware; Mistral Medium 3 is API-only.

Anyone whose priority is strong cost-to-capability at $0.40/$2.00

Mistral Medium 3

It is specifically built for that.

Anyone whose priority is the most capable open-weight model from a us lab (artificial analysis intelligence index of about 48)

NVIDIA Nemotron 3 Ultra

That is its strongest area.

An enterprise with regional data-residency rules

NVIDIA Nemotron 3 Ultra or Mistral Medium 3

Origin (France vs US) affects where data is processed and which compliance regime applies — check the provider's terms for your region.

Mistral Medium 3: where it fits

Mistral's mid-tier model at $0.40/$2.00 — efficient general capability with a 128K window, below the 1M-context frontier tier. Released May 7, 2025 by Mistral AI, it is built for strong cost-to-capability at $0.40/$2.00, general reasoning, coding and multimodal tasks, efficient mid-tier deployment for production workloads, and text and image input.

Its trade-offs are real: a 128K context — smaller than the 1M-window flagships here, no published SWE-Bench Verified score, a mid-tier model, not a frontier reasoner, and proprietary, unlike Mistral's open-weight releases. At $0.4 in / $2 out per million tokens, it sits in the budget price band.

NVIDIA Nemotron 3 Ultra: where it fits

NVIDIA's open-weight reasoning flagship (about 550B total, 55B active) — the most capable open model from a US lab, built for long-running agents. Released June 4, 2026 by NVIDIA, it is built for the most capable open-weight model from a US lab (Artificial Analysis Intelligence Index of about 48), fast, efficient long-horizon agentic reasoning via a hybrid Mamba-Transformer design, a fully open release — weights, training data, and recipes under a permissive license, and strong coding for an open model (SWE-Bench Verified in the high 60s).

Its trade-offs: trails the best Chinese open models on overall intelligence, and a 550B mixture-of-experts is heavy to self-host, and the 1M context is rarely served in full. As an open-weight model, its running cost is your own hardware rather than a per-token fee.

The bottom line for this matchup

The defining split here is open vs. closed. NVIDIA Nemotron 3 Ultra gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Mistral Medium 3 gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.

Want both Mistral Medium 3 and NVIDIA Nemotron 3 Ultra without two subscriptions? LumiChats gives you these plus 40+ models under one ₹69/day pass (about $1/day) — draft with one, cross-check with the other.

See pricing

Frequently asked questions

Is Mistral Medium 3 or NVIDIA Nemotron 3 Ultra better for coding?

Public SWE-Bench figures are not available for either model, so the honest test is your own repository — run an identical real bug through both. By design, Mistral Medium 3 leans toward strong cost-to-capability at $0.40/$2.00 while NVIDIA Nemotron 3 Ultra leans toward the most capable open-weight model from a us lab (artificial analysis intelligence index of about 48), and that positioning usually predicts which feels better on your codebase.

Which is cheaper, Mistral Medium 3 or NVIDIA Nemotron 3 Ultra?

NVIDIA Nemotron 3 Ultra is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Mistral Medium 3 is API-metered at $0.4/$2 per 1M tokens. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.

Which has the bigger context window?

NVIDIA Nemotron 3 Ultra — 1M vs 128K, about 7.8× larger. Useful only if the model actually reasons over the full window, which not all do.

Can I use both Mistral Medium 3 and NVIDIA Nemotron 3 Ultra together?

Yes — a multi-model platform like LumiChats gives you Mistral Medium 3, NVIDIA Nemotron 3 Ultra and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.

Which is newer, Mistral Medium 3 or NVIDIA Nemotron 3 Ultra?

NVIDIA Nemotron 3 Ultra — released June 4, 2026, about 13 months after Mistral Medium 3.

Related comparisons

Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.