AI Models · Open-Source vs Paid

Mistral Medium 3.5 Open vs GPT-5.6 Luna Paid

Mistral Medium 3.5 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 Mistral Medium 3.5 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.

Mistral Medium 3.5 vs GPT-5.6 Luna specs

SpecMistral Medium 3.5GPT-5.6 Luna
MakerMistral AIOpenAI
TypeOpen-weightProprietary
Context window262K tokens1.1M tokens
Input price$1.5/M · free self-host$0.5/M
Output price$7.5/M · free self-host$3/M
Vision / multimodalYesYes
Tool / function callingYesYes
Self-hostableYesNo (API only)
LicenseApache 2.0Proprietary

Feature comparison

CapabilityMistral Medium 3.5GPT-5.6 Luna
Open weights (downloadable)
Self-hostable
Runs fully offline
Vision / multimodal
Tool / function calling
1M+ context window

Benchmarks: Mistral Medium 3.5 vs GPT-5.6 Luna

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

GPT-5.6 Luna delivers 2.3× more intelligence per dollar.
Mistral Medium 3.5
GPT-5.6 Luna
Intelligence index
29.9
51.2
Coding index
46.9
71.4
GPQA
74.8%
91.1%
Humanity's Last Exam
12.8%
37.2%
Long Context Reasoning
61%
74%
SciCode
39.6%
52.5%
IFBench
68.8%
τ²-Bench
94.2%
τ-Bench Banking
14.4%
27.2%
Terminal-Bench
50.6%
80.9%
Terminal-Bench Hard
33.3%
Speed
59.8 tok/s
202.4 tok/s
Latency
0.77s
73.7s
Intelligence per $
10
22.8

Benchmark data by Artificial Analysis.

How Mistral Medium 3.5 and GPT-5.6 Luna score

🏆 Best value & openness: Mistral Medium 3.5 (4.6 vs 3.3 / 5)
CriterionMistral Medium 3.5GPT-5.6 Luna
Cost-efficiency4.04.0
Context window4.05.0
Openness5.01.5
Self-hosting5.01.0
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

Mistral Medium 3.5 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...

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
Mistral Small 4Devstral 2 2512Mistral Large 3 2512Mistral Medium 3.1Mistral Small 3.1 24BMistral Medium 3Ministral 3 14B 2512Mistral Small 3.2 24BMinistral 3 8B 2512Mistral LargeMistral Large 2407Mistral Small 3SabaMinistral 3 3B 2512Mixtral 8x22B InstructCodestral 2508UncensoredVoxtral Small 24B 2507Mistral Nemo

Frequently asked questions

Is Mistral Medium 3.5 as good as GPT-5.6 Luna?

Mistral Medium 3.5 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 Mistral Medium 3.5 locally?

Yes. Mistral Medium 3.5 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.

Mistral Medium 3.5 vs GPT-5.6 Luna — which should I pick in 2026?

Choose Mistral Medium 3.5 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.

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