Pick Mistral Medium 3.5 for strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier or 128b dense open-weight model — self-hostable. 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. On a tight budget at scale, NVIDIA Nemotron 3 Ultra is the value pick.
Mistral Medium 3.5 (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 3.5 is mistral's efficient 128B open-weight model — a single dense model unifying reasoning and coding that punches above its size on independent tests (AA Index 30). 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 and context window — each quantified below from the models' real specs.
Key differences
Context window: NVIDIA Nemotron 3 Ultra holds 3.9× more — 1M (~1,500 pages) vs 256K (~384 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Recency: NVIDIA Nemotron 3 Ultra is the newer model by about 36 days (released June 4, 2026), usually meaning fresher training data and capabilities.
Ecosystem: this is a France-vs-US matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Specifications
Spec
Mistral Medium 3.5
NVIDIA Nemotron 3 Ultra
Provider
Mistral AI (France)
NVIDIA (US)
Released
April 29, 2026
June 4, 2026
Context window
256K (~384 pages)
1M (~1,500 pages)
Price (in/out)
$1.5/$7.5 per 1M tokens
Open weight (self-host / free)
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, image, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Strong intelligence-for-size — Artificial Analysis Intelligence Index 30, near the top of its price tier: Mistral Medium 3.5 — NVIDIA Nemotron 3 Ultra is comparatively weak here — trails the best Chinese open models on overall intelligence
128B dense open-weight model — self-hostable: Mistral Medium 3.5 — Mistral Medium 3.5 lists 128B dense open-weight model — self-hostable among its strengths; NVIDIA Nemotron 3 Ultra does not.
Unifies reasoning and coding into one model with an adjustable reasoning effort: Mistral Medium 3.5 — Mistral Medium 3.5 lists unifies reasoning and coding into one model with an adjustable reasoning effort 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 — 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 — and it carries the larger 1M context.
Fast, efficient long-horizon agentic reasoning via a hybrid Mamba-Transformer design: NVIDIA Nemotron 3 Ultra — Its 1M window holds about 3.9× more than Mistral Medium 3.5's 256K in a single prompt.
A fully open release — weights, training data, and recipes under a permissive license: NVIDIA Nemotron 3 Ultra — Mistral Medium 3.5 is comparatively weak here — license framing ('open' vs enterprise) varies across sources — confirm terms for commercial use
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 3.5's $1.5/$7.5 per 1M tokens.
Largest single-prompt input: NVIDIA Nemotron 3 Ultra — Its 1M window is about 3.9× larger than Mistral Medium 3.5's 256K, 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 3.5, 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.
Anyone whose priority is strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier: Mistral Medium 3.5 — 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 3.5 — Origin (France vs US) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
Mistral Medium 3.5: where it fits
Mistral's efficient 128B open-weight model — a single dense model unifying reasoning and coding that punches above its size on independent tests (AA Index 30). Released April 29, 2026 by Mistral AI, it is built for strong intelligence-for-size — Artificial Analysis Intelligence Index 30, near the top of its price tier, 128B dense open-weight model — self-hostable, unifies reasoning and coding into one model with an adjustable reasoning effort, and 256K context with text and image input.
Its trade-offs are real: below the absolute frontier — a value/efficiency pick, not a flagship-beater, output pricing ($7.50/M) is higher than the cheapest Chinese rivals, license framing ('open' vs enterprise) varies across sources — confirm terms for commercial use, and no native video or audio. At $1.5 in / $7.5 out per million tokens, it sits in the mid 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
This is less "which is smarter" and more "which ecosystem fits." Mistral Medium 3.5 (France) and NVIDIA Nemotron 3 Ultra (US) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. NVIDIA Nemotron 3 Ultra is the cheaper option, which matters at volume. The pragmatic move is to run one real task through both and judge the outputs against your own constraints — including where your data is allowed to be processed.
Frequently asked questions
Is Mistral Medium 3.5 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 3.5 leans toward strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier 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 3.5 or NVIDIA Nemotron 3 Ultra?
NVIDIA Nemotron 3 Ultra is cheaper — $1.5/$7.5 per 1M tokens vs Open weight (self-host / free).
Which has the bigger context window?
NVIDIA Nemotron 3 Ultra — 1M vs 256K, about 3.9× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Mistral Medium 3.5 and NVIDIA Nemotron 3 Ultra together?
Yes — a multi-model platform like LumiChats gives you Mistral Medium 3.5, 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 3.5 or NVIDIA Nemotron 3 Ultra?
NVIDIA Nemotron 3 Ultra — released June 4, 2026, about 36 days after Mistral Medium 3.5.
Mistral Medium 3.5 vs NVIDIA Nemotron 3 Ultra
Mistral AI · France | NVIDIA · US · Updated June 2026
Quick verdict
Pick Mistral Medium 3.5 for strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier or 128b dense open-weight model — self-hostable. 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. On a tight budget at scale, NVIDIA Nemotron 3 Ultra is the value pick.
Mistral Medium 3.5 (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 3.5 is mistral's efficient 128B open-weight model — a single dense model unifying reasoning and coding that punches above its size on independent tests (AA Index 30). 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 and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Context window: NVIDIA Nemotron 3 Ultra holds 3.9× more — 1M (~1,500 pages) vs 256K (~384 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Recency: NVIDIA Nemotron 3 Ultra is the newer model by about 36 days (released June 4, 2026), usually meaning fresher training data and capabilities.
▸Ecosystem: this is a France-vs-US matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
Spec
Mistral Medium 3.5
NVIDIA Nemotron 3 Ultra
Provider
Mistral AI (France)
NVIDIA (US)
Released
April 29, 2026
June 4, 2026
Context window
256K (~384 pages)
1M (~1,500 pages)
Price (in/out)
$1.5/$7.5 per 1M tokens
Open weight (self-host / free)
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, image, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Strong intelligence-for-size — Artificial Analysis Intelligence Index 30, near the top of its price tier
Mistral Medium 3.5
NVIDIA Nemotron 3 Ultra is comparatively weak here — trails the best Chinese open models on overall intelligence
128B dense open-weight model — self-hostable
Mistral Medium 3.5
Mistral Medium 3.5 lists 128B dense open-weight model — self-hostable among its strengths; NVIDIA Nemotron 3 Ultra does not.
Unifies reasoning and coding into one model with an adjustable reasoning effort
Mistral Medium 3.5
Mistral Medium 3.5 lists unifies reasoning and coding into one model with an adjustable reasoning effort 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
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 — and it carries the larger 1M context.
Fast, efficient long-horizon agentic reasoning via a hybrid Mamba-Transformer design
NVIDIA Nemotron 3 Ultra
Its 1M window holds about 3.9× more than Mistral Medium 3.5's 256K in a single prompt.
A fully open release — weights, training data, and recipes under a permissive license
NVIDIA Nemotron 3 Ultra
Mistral Medium 3.5 is comparatively weak here — license framing ('open' vs enterprise) varies across sources — confirm terms for commercial use
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 3.5's $1.5/$7.5 per 1M tokens.
Largest single-prompt input
NVIDIA Nemotron 3 Ultra
Its 1M window is about 3.9× larger than Mistral Medium 3.5's 256K, 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 3.5, 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.
Anyone whose priority is strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier
→ Mistral Medium 3.5
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 3.5
Origin (France vs US) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
Mistral Medium 3.5: where it fits
Mistral's efficient 128B open-weight model — a single dense model unifying reasoning and coding that punches above its size on independent tests (AA Index 30). Released April 29, 2026 by Mistral AI, it is built for strong intelligence-for-size — Artificial Analysis Intelligence Index 30, near the top of its price tier, 128B dense open-weight model — self-hostable, unifies reasoning and coding into one model with an adjustable reasoning effort, and 256K context with text and image input.
Its trade-offs are real: below the absolute frontier — a value/efficiency pick, not a flagship-beater, output pricing ($7.50/M) is higher than the cheapest Chinese rivals, license framing ('open' vs enterprise) varies across sources — confirm terms for commercial use, and no native video or audio. At $1.5 in / $7.5 out per million tokens, it sits in the mid 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
This is less "which is smarter" and more "which ecosystem fits." Mistral Medium 3.5 (France) and NVIDIA Nemotron 3 Ultra (US) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. NVIDIA Nemotron 3 Ultra is the cheaper option, which matters at volume. The pragmatic move is to run one real task through both and judge the outputs against your own constraints — including where your data is allowed to be processed.
Want both Mistral Medium 3.5 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.
Is Mistral Medium 3.5 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 3.5 leans toward strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier 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 3.5 or NVIDIA Nemotron 3 Ultra?
NVIDIA Nemotron 3 Ultra is cheaper — $1.5/$7.5 per 1M tokens vs Open weight (self-host / free).
Which has the bigger context window?
NVIDIA Nemotron 3 Ultra — 1M vs 256K, about 3.9× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Mistral Medium 3.5 and NVIDIA Nemotron 3 Ultra together?
Yes — a multi-model platform like LumiChats gives you Mistral Medium 3.5, 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 3.5 or NVIDIA Nemotron 3 Ultra?
NVIDIA Nemotron 3 Ultra — released June 4, 2026, about 36 days after Mistral Medium 3.5.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.