Jamba2 Mini vs Mistral Medium 3.5

AI21 Labs · Israel  |  Mistral AI · France · Updated June 2026

Quick verdict

Pick Jamba2 Mini for a genuinely different architecture - hybrid mamba (ssm) + transformer, not another transformer variant or fast, efficient long-context inference tuned for enterprise workloads. 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. On a tight budget at scale, Jamba2 Mini is the value pick.

Jamba2 Mini (AI21 Labs, Israel) and Mistral Medium 3.5 (Mistral AI, France) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. Jamba2 Mini is aI21's hybrid Mamba-Transformer model - a genuinely different architecture built for fast, efficient long-context enterprise work, free to self-host under Apache 2.0. 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). They diverge most on price and context window — each quantified below from the models' real specs.

Key differences at a glance

Side-by-side specs

SpecJamba2 MiniMistral Medium 3.5
ProviderAI21 Labs (Israel) Mistral AI (France)
ReleasedJanuary 8, 2026 April 28, 2026
Context window256K (~393 pages) 256K (~384 pages)
Price (in/out)Open weight (self-host / free) $1.5/$7.5 per 1M tokens
Open weight?Yes — self-hostable Yes — self-hostable
Modalitiestext, code text, image, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

A genuinely different architecture - hybrid Mamba (SSM) + Transformer, not another transformer variant

Jamba2 Mini

Jamba2 Mini lists a genuinely different architecture - hybrid Mamba (SSM) + Transformer, not another transformer variant among its strengths; Mistral Medium 3.5 does not.

Fast, efficient long-context inference tuned for enterprise workloads

Jamba2 Mini

Mistral Medium 3.5 is comparatively weak here — license framing ('open' vs enterprise) varies across sources — confirm terms for commercial use

Open weights (Apache 2.0) - free to self-host

Jamba2 Mini

Jamba2 Mini lists open weights (Apache 2.0) - free to self-host among its strengths; Mistral Medium 3.5 does not.

Strong intelligence-for-size — Artificial Analysis Intelligence Index 30, near the top of its price tier

Mistral Medium 3.5

Jamba2 Mini is comparatively weak here — no official per-token API price published - self-host or use AI21's platform preview

128B dense open-weight model — self-hostable

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.

Unifies reasoning and coding into one model with an adjustable reasoning effort

Mistral Medium 3.5

Jamba2 Mini is comparatively weak here — tuned for grounded, steerable enterprise tasks rather than topping general reasoning leaderboards

Lowest cost at scale

Jamba2 Mini

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.

Which should you pick?

A cost-sensitive startup shipping high volume

Jamba2 Mini

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

Jamba2 Mini

Larger 256K window fits more in one prompt.

Anyone whose priority is a genuinely different architecture - hybrid mamba (ssm) + transformer, not another transformer variant

Jamba2 Mini

It is specifically built for that.

Anyone whose priority is strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier

Mistral Medium 3.5

That is its strongest area.

An enterprise with regional data-residency rules

Mistral Medium 3.5 or Jamba2 Mini

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

Jamba2 Mini: where it fits

AI21's hybrid Mamba-Transformer model - a genuinely different architecture built for fast, efficient long-context enterprise work, free to self-host under Apache 2.0. Released January 8, 2026 by AI21 Labs, it is built for a genuinely different architecture - hybrid Mamba (SSM) + Transformer, not another transformer variant, fast, efficient long-context inference tuned for enterprise workloads, open weights (Apache 2.0) - free to self-host, and a 52B-total/12B-active MoE design that's cheap to run relative to its capability.

Its trade-offs are real: tuned for grounded, steerable enterprise tasks rather than topping general reasoning leaderboards, no official per-token API price published - self-host or use AI21's platform preview, and newer architecture family means less third-party tooling support than mainstream transformers. As an open-weight model, its running cost is your own hardware rather than a per-token fee.

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 28, 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: 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.

The bottom line for this matchup

This is less "which is smarter" and more "which ecosystem fits." Jamba2 Mini (Israel) and Mistral Medium 3.5 (France) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. Jamba2 Mini 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 Jamba2 Mini and Mistral Medium 3.5 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 Jamba2 Mini or Mistral Medium 3.5 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, Jamba2 Mini leans toward a genuinely different architecture - hybrid mamba (ssm) + transformer, not another transformer variant while Mistral Medium 3.5 leans toward strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier, and that positioning usually predicts which feels better on your codebase.

Which is cheaper, Jamba2 Mini or Mistral Medium 3.5?

Jamba2 Mini is cheaper — Open weight (self-host / free) vs $1.5/$7.5 per 1M tokens.

Which has the bigger context window?

Effectively neither — 256K vs 256K is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.

Can I use both Jamba2 Mini and Mistral Medium 3.5 together?

Yes — a multi-model platform like LumiChats gives you Jamba2 Mini, Mistral Medium 3.5 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, Jamba2 Mini or Mistral Medium 3.5?

Mistral Medium 3.5 — released April 28, 2026, about 4 months after Jamba2 Mini.

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.