AI Models · Open-Source vs Paid

Granite 4.0 Micro Open vs Gemini 3.1 Pro Preview Paid

Granite 4.0 Micro vs Gemini 3.1 Pro Preview 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 · OpenSourceAI.tech

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

Choose Granite 4.0 Micro 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.

Granite 4.0 Micro vs Gemini 3.1 Pro Preview specs

SpecGranite 4.0 MicroGemini 3.1 Pro Preview
MakerIBMGoogle
TypeOpen-weightProprietary
Context window131K tokens1M tokens
Input price$0.02/M · free self-host$2/M
Output price$0.11/M · free self-host$12/M
Vision / multimodalNoYes
Tool / function callingNoYes
Self-hostableYesNo (API only)
LicenseApache 2.0Proprietary

Feature comparison

CapabilityGranite 4.0 MicroGemini 3.1 Pro Preview
Open weights (downloadable)
Self-hostable
Runs fully offline
Vision / multimodal
Tool / function calling
1M+ context window

Benchmarks: Granite 4.0 Micro vs Gemini 3.1 Pro Preview

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

Granite 4.0 Micro
Gemini 3.1 Pro Preview
Intelligence index
2.4
46.5
Math index
6
GPQA
33.6%
94.1%
MMLU-Pro
44.7%
Humanity's Last Exam
5.1%
44.7%
Long Context Reasoning
4%
72.7%
LiveCodeBench
18%
SciCode
11.9%
58.9%
AIME 2025
6%
IFBench
24.8%
77.1%
τ²-Bench
12.6%
95.6%
Terminal-Bench Hard
1.5%
53.8%
Coding index
68.8
τ-Bench Banking
16.5%
Terminal-Bench
73.8%
Speed
0 tok/s
137.1 tok/s
Latency
0s
23.58s
Intelligence per $
10.3

Benchmark data by Artificial Analysis.

How Granite 4.0 Micro and Gemini 3.1 Pro Preview score

🏆 Best value & openness: Granite 4.0 Micro (4.1 vs 3.2 / 5)
CriterionGranite 4.0 MicroGemini 3.1 Pro Preview
Cost-efficiency5.03.5
Context window3.55.0
Openness5.01.5
Self-hosting5.01.0
Multimodality2.05.0

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

Granite 4.0 Micro Open

IBM · Open-weight

Granite-4.0-H-Micro is a 3B parameter from the Granite 4 family of models. These models are the latest in a series of models released by IBM. They are fine-tuned for long...

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.

Other models in these families

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

Other variants tracked
Granite 4.1 8B
Other variants tracked
Gemini 2.5 Pro

Frequently asked questions

Is Granite 4.0 Micro as good as Gemini 3.1 Pro Preview?

Granite 4.0 Micro 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 Granite 4.0 Micro locally?

Yes. Granite 4.0 Micro 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 Granite 4.0 Micro?

Granite 4.0 Micro costs $0.11/M output vs $12/M for Gemini 3.1 Pro Preview — roughly 109x cheaper via API, and free if you self-host.

Granite 4.0 Micro vs Gemini 3.1 Pro Preview — which should I pick in 2026?

Choose Granite 4.0 Micro 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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