AI Models · Open-Source vs Paid

Gemini 3.1 Pro Preview Paid vs Mistral Medium 3.5 (batch) Open

Gemini 3.1 Pro Preview 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.

Prices & specs refreshed from live data · olud.ai

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

Gemini 3.1 Pro PreviewPaidGoogle
$2 /M input
$12 /M outputManaged API (no infra to run)
TypeProprietary
Context window1M 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 Gemini 3.1 Pro Preview if you want frontier capability through a managed API with zero infrastructure to run.

Gemini 3.1 Pro Preview vs Mistral Medium 3.5 (batch) specs

SpecGemini 3.1 Pro PreviewMistral Medium 3.5 (batch)Winner
MakerGoogleMistral AI
TypeProprietaryOpen-weightMistral Medium 3.5 (batch)
Context window1M tokens262K tokensGemini 3.1 Pro Preview
Input price$2/M$0.75/M · free self-hostMistral Medium 3.5 (batch)
Output price$12/M$3.75/M · free self-hostMistral Medium 3.5 (batch)
Vision / multimodalYesYes= Tie
Tool / function callingYesYes= Tie
Self-hostableNo (API only)YesMistral Medium 3.5 (batch)
LicenseProprietaryApache 2.0Mistral Medium 3.5 (batch)

Price gap & when to choose each

3.2×cheaper per output token

Mistral Medium 3.5 (batch) is ~3.2× cheaper than Gemini 3.1 Pro Preview on output tokens ($3.75 vs $12 per M tokens).

Choose Gemini 3.1 Pro Preview if…
  • You want frontier performance through a managed API
  • You need the longer 1M context window
  • 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 prioritize data privacy & control
  • You want the lowest operating costs
  • You are building open or reproducible AI

Feature comparison

CapabilityGemini 3.1 Pro PreviewMistral Medium 3.5 (batch)
Open weights (downloadable)
Self-hostable
Runs fully offline
Vision / multimodal
Tool / function calling
1M+ context window

Benchmarks: Gemini 3.1 Pro Preview vs Mistral Medium 3.5 (batch)

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

Gemini 3.1 Pro Preview
Mistral Medium 3.5 (batch)
Intelligence index
30.4
14.9
Coding index
68.8
46.9
GPQA
94.1%
74.8%
Humanity's Last Exam
47%
13.8%
Long Context Reasoning
82%
69.3%
SciCode
58.7%
40.2%
IFBench
77.1%
68.8%
τ²-Bench
95.6%
94.2%
τ-Bench Banking
21.4%
15.1%
Terminal-Bench
73.8%
50.6%
Terminal-Bench Hard
53.8%
33.3%
Speed
125.2 tok/s
142.2 tok/s
Latency
24.48s
0.74s
Intelligence per $
6.8
5

Benchmark data by Artificial Analysis.

How Gemini 3.1 Pro Preview and Mistral Medium 3.5 (batch) score

🏆 Best value & openness: Mistral Medium 3.5 (batch) (4.6 vs 3.2 / 5)
CriterionGemini 3.1 Pro PreviewMistral Medium 3.5 (batch)
Cost-efficiency3.54.0
Context window5.04.0
Openness1.55.0
Self-hosting1.05.0
Multimodality5.05.0

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

Gemini 3.1 Pro Preview Paid

Google · Proprietary

Gemini 3.1 Pro Preview is Google’s frontier reasoning model, delivering enhanced software engineering performance, improved agentic reliability, and more efficient token usage across complex workflows. Building on the multimodal foundation.

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
Gemini 3.1 Pro Preview (batch)Gemini 2.5 ProGemini 2.5 Pro (batch)Gemini 2.5 Pro Preview 05-06Gemini 3.1 Pro Preview Custom ToolsNano Banana Pro (Gemini 3 Pro Image Preview)
Other variants tracked
Mistral Medium 3.5Mistral Small 4Mistral Small 4 (batch)Mistral Medium 3.1Mistral Medium 3.1 (batch)Mistral Large 3 2512Mistral Large 3 2512 (batch)Devstral 2 2512Mistral Medium 3Mistral Small 3.1 24BMistral Small 3.2 24BMistral LargeMistral Large 2407Mistral Small 3SabaMinistral 3 14B 2512Mixtral 8x22B InstructMinistral 3 8B 2512Ministral 3 8B 2512 (batch)Ministral 3 3B 2512UncensoredCodestral 2508Codestral 2508 (batch)Voxtral Small 24B 2507Mistral Nemo

Frequently asked questions

Is Mistral Medium 3.5 (batch) as good as Gemini 3.1 Pro Preview?

Mistral Medium 3.5 (batch) is open-weight and competitive on many tasks, but Gemini 3.1 Pro Preview 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. Gemini 3.1 Pro Preview 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 $12/M for Gemini 3.1 Pro Preview — roughly 3x cheaper via API, and free if you self-host.

Gemini 3.1 Pro Preview 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 Gemini 3.1 Pro Preview if you want frontier capability through a managed API with zero infrastructure to run.

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