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 Mistral NeMo for multilingual understanding across 11+ languages or runs on a single gpu with fp8 quantization-aware training. On a tight budget at scale, Mistral NeMo is the value pick.
Mistral Medium 3.5 (Mistral AI) and Mistral NeMo (Mistral) are two of the models people most often weigh against each other in 2026. 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). Mistral NeMo is a 12B Apache-2.0 open-weight model co-developed by Mistral and NVIDIA, pairing a 128K context and strong multilingual performance with efficiency that fits on a single GPU. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Price: Mistral NeMo is about 75× cheaper on input ($0.02/$0.03 per 1M tokens vs $1.5/$7.5 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
Context window: Mistral Medium 3.5 holds 2× more — 256K (~384 pages) vs 128K (~197 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Recency: Mistral Medium 3.5 is the newer model by about 22 months (released April 29, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Mistral Medium 3.5
Mistral NeMo
Provider
Mistral AI (France)
Mistral (France)
Released
April 29, 2026
July 18, 2024
Context window
256K (~384 pages)
128K (~197 pages)
Price (in/out)
$1.5/$7.5 per 1M tokens
$0.02/$0.03 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, image, code
text
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 — 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) — and it carries the larger 256K context.
128B dense open-weight model — self-hostable: Mistral Medium 3.5 — Mistral NeMo is comparatively weak here — 12B scale trails larger frontier models on complex reasoning and coding
Unifies reasoning and coding into one model with an adjustable reasoning effort: Mistral Medium 3.5 — 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) — and it is the newer of the two.
Multilingual understanding across 11+ languages: Mistral NeMo — Mistral Medium 3.5 is comparatively weak here — license framing ('open' vs enterprise) varies across sources — confirm terms for commercial use
Runs on a single GPU with FP8 quantization-aware training: Mistral NeMo — A 12B Apache-2.0 open-weight model co-developed by Mistral and NVIDIA, pairing a 128K context and strong multilingual performance with efficiency that fits on a single GPU — and it runs cheaper at $0.02/$0.03 per 1M tokens.
128K-token context for long documents: Mistral NeMo — Mistral NeMo lists 128K-token context for long documents among its strengths; Mistral Medium 3.5 does not.
Lowest cost at scale: Mistral NeMo — At $0.02/$0.03 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: Mistral Medium 3.5 — Its 256K window is about 2× larger than Mistral NeMo's 128K, fitting roughly 384 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: Mistral NeMo — At $0.02/$0.03 per 1M tokens it undercuts Mistral Medium 3.5, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Mistral Medium 3.5 — Larger 256K 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 multilingual understanding across 11+ languages: Mistral NeMo — That is its strongest area.
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.
Mistral NeMo: where it fits
A 12B Apache-2.0 open-weight model co-developed by Mistral and NVIDIA, pairing a 128K context and strong multilingual performance with efficiency that fits on a single GPU. Released July 18, 2024 by Mistral, it is built for multilingual understanding across 11+ languages, runs on a single GPU with FP8 quantization-aware training, 128K-token context for long documents, and function calling and structured tool use.
Its trade-offs: 12B scale trails larger frontier models on complex reasoning and coding, and text-only; no vision or audio input. At $0.02 in / $0.03 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Mistral Medium 3.5 and Mistral NeMo overlap enough that the right pick depends on your specific job. Mistral NeMo costs less per token; Mistral Medium 3.5 holds the larger context; and each leads in its own area — Mistral Medium 3.5 for strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier, Mistral NeMo for multilingual understanding across 11+ languages. Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is Mistral Medium 3.5 or Mistral NeMo 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 Mistral NeMo leans toward multilingual understanding across 11+ languages, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Mistral Medium 3.5 or Mistral NeMo?
Mistral NeMo is cheaper — $1.5/$7.5 per 1M tokens vs $0.02/$0.03 per 1M tokens, roughly 75× apart on input.
Which has the bigger context window?
Mistral Medium 3.5 — 256K vs 128K, about 2× 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 Mistral NeMo together?
Yes — a multi-model platform like LumiChats gives you Mistral Medium 3.5, Mistral NeMo 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 Mistral NeMo?
Mistral Medium 3.5 — released April 29, 2026, about 22 months after Mistral NeMo.
Mistral Medium 3.5 vs Mistral NeMo
Mistral AI · France | Mistral · France · 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 Mistral NeMo for multilingual understanding across 11+ languages or runs on a single gpu with fp8 quantization-aware training. On a tight budget at scale, Mistral NeMo is the value pick.
Mistral Medium 3.5 (Mistral AI) and Mistral NeMo (Mistral) are two of the models people most often weigh against each other in 2026. 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). Mistral NeMo is a 12B Apache-2.0 open-weight model co-developed by Mistral and NVIDIA, pairing a 128K context and strong multilingual performance with efficiency that fits on a single GPU. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Price: Mistral NeMo is about 75× cheaper on input ($0.02/$0.03 per 1M tokens vs $1.5/$7.5 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
▸Context window: Mistral Medium 3.5 holds 2× more — 256K (~384 pages) vs 128K (~197 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Recency: Mistral Medium 3.5 is the newer model by about 22 months (released April 29, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Mistral Medium 3.5
Mistral NeMo
Provider
Mistral AI (France)
Mistral (France)
Released
April 29, 2026
July 18, 2024
Context window
256K (~384 pages)
128K (~197 pages)
Price (in/out)
$1.5/$7.5 per 1M tokens
$0.02/$0.03 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, image, code
text
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
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) — and it carries the larger 256K context.
128B dense open-weight model — self-hostable
Mistral Medium 3.5
Mistral NeMo is comparatively weak here — 12B scale trails larger frontier models on complex reasoning and coding
Unifies reasoning and coding into one model with an adjustable reasoning effort
Mistral Medium 3.5
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) — and it is the newer of the two.
Multilingual understanding across 11+ languages
Mistral NeMo
Mistral Medium 3.5 is comparatively weak here — license framing ('open' vs enterprise) varies across sources — confirm terms for commercial use
Runs on a single GPU with FP8 quantization-aware training
Mistral NeMo
A 12B Apache-2.0 open-weight model co-developed by Mistral and NVIDIA, pairing a 128K context and strong multilingual performance with efficiency that fits on a single GPU — and it runs cheaper at $0.02/$0.03 per 1M tokens.
128K-token context for long documents
Mistral NeMo
Mistral NeMo lists 128K-token context for long documents among its strengths; Mistral Medium 3.5 does not.
Lowest cost at scale
Mistral NeMo
At $0.02/$0.03 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
Mistral Medium 3.5
Its 256K window is about 2× larger than Mistral NeMo's 128K, fitting roughly 384 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Mistral NeMo
At $0.02/$0.03 per 1M tokens it undercuts Mistral Medium 3.5, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Mistral Medium 3.5
Larger 256K 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 multilingual understanding across 11+ languages
→ Mistral NeMo
That is its strongest area.
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.
Mistral NeMo: where it fits
A 12B Apache-2.0 open-weight model co-developed by Mistral and NVIDIA, pairing a 128K context and strong multilingual performance with efficiency that fits on a single GPU. Released July 18, 2024 by Mistral, it is built for multilingual understanding across 11+ languages, runs on a single GPU with FP8 quantization-aware training, 128K-token context for long documents, and function calling and structured tool use.
Its trade-offs: 12B scale trails larger frontier models on complex reasoning and coding, and text-only; no vision or audio input. At $0.02 in / $0.03 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Mistral Medium 3.5 and Mistral NeMo overlap enough that the right pick depends on your specific job. Mistral NeMo costs less per token; Mistral Medium 3.5 holds the larger context; and each leads in its own area — Mistral Medium 3.5 for strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier, Mistral NeMo for multilingual understanding across 11+ languages. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both Mistral Medium 3.5 and Mistral NeMo 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 Mistral NeMo 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 Mistral NeMo leans toward multilingual understanding across 11+ languages, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Mistral Medium 3.5 or Mistral NeMo?
Mistral NeMo is cheaper — $1.5/$7.5 per 1M tokens vs $0.02/$0.03 per 1M tokens, roughly 75× apart on input.
Which has the bigger context window?
Mistral Medium 3.5 — 256K vs 128K, about 2× 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 Mistral NeMo together?
Yes — a multi-model platform like LumiChats gives you Mistral Medium 3.5, Mistral NeMo 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 Mistral NeMo?
Mistral Medium 3.5 — released April 29, 2026, about 22 months after Mistral NeMo.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.