AI Models · Open-Source vs Paid

Granite 4.1 8B Open vs GPT-5.6 Luna Paid

Granite 4.1 8B vs GPT-5.6 Luna 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.

Choose Granite 4.1 8B 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 GPT-5.6 Luna if you want frontier capability through a managed API with zero infrastructure to run.

Granite 4.1 8B vs GPT-5.6 Luna specs

SpecGranite 4.1 8BGPT-5.6 Luna
MakerIBMOpenAI
TypeOpen-weightProprietary
Context window131K tokens1.1M tokens
Input price$0.05/M · free self-host$0.5/M
Output price$0.1/M · free self-host$3/M
Vision / multimodalNoYes
Tool / function callingYesYes
Self-hostableYesNo (API only)
LicenseApache 2.0Proprietary

Feature comparison

CapabilityGranite 4.1 8BGPT-5.6 Luna
Open weights (downloadable)
Self-hostable
Runs fully offline
Vision / multimodal
Tool / function calling
1M+ context window

Benchmarks: Granite 4.1 8B vs GPT-5.6 Luna

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

Granite 4.1 8B delivers 4.7× more intelligence per dollar.
Granite 4.1 8B
GPT-5.6 Luna
Intelligence index
6.7
51.2
Coding index
9.5
71.4
GPQA
43.3%
91.1%
Humanity's Last Exam
3.8%
37.2%
Long Context Reasoning
12%
74%
SciCode
21.8%
52.5%
IFBench
38.6%
τ²-Bench
27.8%
τ-Bench Banking
3.1%
27.2%
Terminal-Bench
3.4%
80.9%
Terminal-Bench Hard
0%
Speed
104.8 tok/s
202.4 tok/s
Latency
0.44s
73.7s
Intelligence per $
106.3
22.8

Benchmark data by Artificial Analysis.

How Granite 4.1 8B and GPT-5.6 Luna score

🏆 Best value & openness: Granite 4.1 8B (4.4 vs 3.3 / 5)
CriterionGranite 4.1 8BGPT-5.6 Luna
Cost-efficiency5.04.0
Context window3.55.0
Openness5.01.5
Self-hosting5.01.0
Multimodality3.55.0

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 4.1 8B Open

IBM · Open-weight

Granite 4.1 8B is a dense, decoder-only 8-billion-parameter language model from IBM, part of the Granite 4.1 family. It supports a 131K-token context window and is designed for enterprise tasks...

GPT-5.6 Luna Paid

OpenAI · Proprietary

GPT-5.6 Luna is a fast, cost-efficient model in OpenAI's GPT-5.6 series. It is suited for high-volume, latency-sensitive tasks such as chat, classification, and lightweight agentic workflows, providing capable reasoning for...

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 4.0 Micro

Frequently asked questions

Is Granite 4.1 8B as good as GPT-5.6 Luna?

Granite 4.1 8B is open-weight and competitive on many tasks, but GPT-5.6 Luna 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 4.1 8B locally?

Yes. Granite 4.1 8B has open weights, so you can self-host it on your own GPUs or run it via a low-cost API. GPT-5.6 Luna is API-only and cannot be self-hosted.

How much cheaper is Granite 4.1 8B?

Granite 4.1 8B costs $0.1/M output vs $3/M for GPT-5.6 Luna — roughly 30x cheaper via API, and free if you self-host.

Granite 4.1 8B vs GPT-5.6 Luna — which should I pick in 2026?

Choose Granite 4.1 8B 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 GPT-5.6 Luna if you want frontier capability through a managed API with zero infrastructure to run.

People also compare

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 →