AI Models · Open-Source vs Paid

Nano Banana 2.1 Paid vs Mistral Medium 3.5 (batch) Open

Nano Banana 2.1 vs Mistral Medium 3.5 (batch) compared — price per token, context window, multimodality, openness and which to choose. Can the open-source model replace the paid one? Full 2026 breakdown.

Nano Banana 2.1 — full profile ›

Prices & specs refreshed from live data · olud.ai

Open-model prices = cheapest provider via OpenRouter; official maker rates may be higher.

Nano Banana 2.1PaidGoogle

$1.5 /M input
$7.5 /M outputManaged API (no infra to run)

TypeProprietary

Context window66K tokens

MultimodalYes

Self-hostNo

Mistral Medium 3.5 (batch)OpenMistral AI

$0.75 /M input
$3.75 /M outputNo per-token fees if you self-host

TypeOpen-weight

Context window262K tokens

MultimodalYes

Self-hostYes

Choose Mistral Medium 3.5 (batch) if you want to self-host, keep your data private and skip per-token fees — it's open-weight and runs on your own hardware. Choose Nano Banana 2.1 if you want frontier capability through a managed API with zero infrastructure to run.

Nano Banana 2.1 vs Mistral Medium 3.5 (batch) specs

Spec	Nano Banana 2.1	Mistral Medium 3.5 (batch)	Winner
Maker	Google	Mistral AI	–
Type	Proprietary	Open-weight	Mistral Medium 3.5 (batch)
Context window	66K tokens	262K tokens	Mistral Medium 3.5 (batch)
Input price	$1.5/M	$0.75/M · free self-host	Mistral Medium 3.5 (batch)
Output price	$7.5/M	$3.75/M · free self-host	Mistral Medium 3.5 (batch)
Vision / multimodal	Yes	Yes	= Tie
Tool / function calling	Yes	Yes	= Tie
Self-hostable	No (API only)	Yes	Mistral Medium 3.5 (batch)
License	Proprietary	Apache 2.0	Mistral Medium 3.5 (batch)

Price gap & when to choose each

2.0×cheaper per output token

Mistral Medium 3.5 (batch) is ~2.0× cheaper than Nano Banana 2.1 on output tokens ($3.75 vs $7.5 per M tokens).

Choose Nano Banana 2.1 if…

You want frontier performance through a managed API
You value reliability & ecosystem
You don't want to manage infrastructure

Choose Mistral Medium 3.5 (batch) if…

You want to self-host or run on your cloud
You need the longer 262K context window
You prioritize data privacy & control
You want the lowest operating costs
You are building open or reproducible AI

Feature comparison

Capability	Nano Banana 2.1	Mistral Medium 3.5 (batch)
Open weights (downloadable)	✗	✓
Self-hostable	✗	✓
Runs fully offline	✗	✓
Vision / multimodal	✓	✓
Tool / function calling	✓	✓
1M+ context window	✗	✗

Benchmarks: Nano Banana 2.1 vs Mistral Medium 3.5 (batch)

Independent benchmark scores measured by Artificial Analysis. Higher is better (except latency).

Nano Banana 2.1

Mistral Medium 3.5 (batch)

Intelligence index

–

14.2

Coding index

–

46.9

GPQA

–

74.8%

Humanity's Last Exam

–

13.8%

Long Context Reasoning

–

69.3%

SciCode

–

40.2%

IFBench

–

68.8%

τ²-Bench

–

94.2%

τ-Bench Banking

–

15.1%

Terminal-Bench

–

50.6%

Terminal-Bench Hard

–

33.3%

Speed

–

174.8 tok/s

Latency

–

0.61s

Intelligence per $

–

4.7

Benchmark data by Artificial Analysis.

How Nano Banana 2.1 and Mistral Medium 3.5 (batch) score

🏆 Best value & openness: Mistral Medium 3.5 (batch) (4.6 vs 2.9 / 5)

Criterion	Nano Banana 2.1	Mistral Medium 3.5 (batch)
Cost-efficiency	4.0	4.0
Context window	3.0	4.0
Openness	1.5	5.0
Self-hosting	1.0	5.0
Multimodality	5.0	5.0

Scores come from live data — output price (cost), context length, open vs closed weights (openness & self-hosting) and vision/tool support (multimodality). Raw task quality isn't scored here; it depends on your benchmark — see the verdict.

What each model is

Nano Banana 2.1 Paid

Google · Proprietary

Nano Banana 2.1 (Gemini Nano Banana 2.1) is Google's image generation and editing model on the Flash tier, succeeding Nano Banana 2 and Nano Banana Pro. It improves product recontextualization,...

Mistral Medium 3.5 (batch) Open

Mistral AI · Open-weight

Mistral Medium 3.5 is a dense 128B instruction-following model from Mistral AI. It supports text and image inputs with text output, and is designed for agentic workflows, coding, and complex...

Other models in these families

These variants are tracked but not compared here — one page per family keeps the comparison readable.

Other variants tracked

Mistral Large 4Mistral Medium 3.5Mistral Small 4Mistral Large 3 2512Mistral Medium 3.1Mistral Medium 3Devstral 2 2512Mistral Small 3.1 24BMistral Small 3.2 24BMistral LargeMistral Large 2407Mistral Small 3SabaMinistral 3 14B 2512Mixtral 8x22B InstructMinistral 3 8B 2512Ministral 3 3B 2512UncensoredCodestral 2508Voxtral Small 24B 2507Mistral Nemo

Frequently asked questions

Is Mistral Medium 3.5 (batch) as good as Nano Banana 2.1?

Mistral Medium 3.5 (batch) is open-weight and competitive on many tasks, but Nano Banana 2.1 may still lead on the hardest reasoning and agentic work. The gap keeps narrowing — benchmark both on your actual use case before deciding.

Can I run Mistral Medium 3.5 (batch) locally?

Yes. Mistral Medium 3.5 (batch) has open weights, so you can self-host it on your own GPUs or run it via a low-cost API. Nano Banana 2.1 is API-only and cannot be self-hosted.

How much cheaper is Mistral Medium 3.5 (batch)?

Mistral Medium 3.5 (batch) costs $3.75/M output vs $7.5/M for Nano Banana 2.1 — roughly 2x cheaper via API, and free if you self-host.

Nano Banana 2.1 vs Mistral Medium 3.5 (batch) — which should I pick in 2026?

Choose Mistral Medium 3.5 (batch) if you want to self-host, keep your data private and skip per-token fees — it's open-weight and runs on your own hardware. Choose Nano Banana 2.1 if you want frontier capability through a managed API with zero infrastructure to run.

People also compare

DeepSeek V4.1 Flash 1017 vs Nano Banana 2.1 DeepSeek V4.1 Flash 1017 vs Mistral Medium 3.5 (batch)GLM 5.3 (batch) vs Nano Banana 2.1 GLM 5.3 (batch) vs Mistral Medium 3.5 (batch)Hy3 vs Nano Banana 2.1 Hy3 vs Mistral Medium 3.5 (batch)

Explore more open-source AI

Browse the full open-source model leaderboard, thousands of tools and live benchmarks — all in one place.

Open the leaderboard →