// head_to_head
MiniMax M3.1 Flash vs Llama 3 8B Lunaris
Published LiveBench scores across all seven categories, live list pricing, context windows, and the measured cost of a point of capability — for both models, side by side.
Llama 3 8B Lunaris is the cheaper of the two; neither can be ranked on quality here.
Llama 3 8B Lunaris does not have a published LiveBench run, so this comparison covers price, context and declared capabilities only. A missing score means "not evaluated", not "worse" — the right way to separate these two is an eval on your own workload.
minimax
MiniMax M3.1 Flash
- Blended / 1M
- $0.131
- Context
- 1.0M
- Released
- Oct 19, 2026
- Overall score
- 66.9
Specs and pricing
| Metric | MiniMax M3.1 Flash | Llama 3 8B Lunaris |
|---|---|---|
| LiveBench overall Weighted mean of the seven LiveBench category scores, 0–100. Higher is better. | 66.9 | — |
| Cost per point Measured benchmark spend divided by overall score — dollars per point of capability. | $0.0015 | — |
| Blended price / 1M 3:1 input:output mix, the usual shape of production traffic. | $0.131 | $0.042win |
| Input price / 1M | $0.075 | $0.040win |
| Output price / 1M | $0.300 | $0.050win |
| Cached input / 1M Price of an input token served from the prompt cache, where the provider publishes one. | $0.0075 | — |
| Context window | 1.0Mwin | 8K |
| Max output tokens | 524Kwin | 7K |
Benchmarks by category
An overall score averages away the thing you probably care about. These are the seven LiveBench categories scored separately — MiniMax M3.1 Flash on top, Llama 3 8B Lunaris below, both out of 100.
What each one costs to run
Per-token prices are hard to feel. These are monthly list costs for both models across five workload shapes, using each provider's published cached-input rate where there is one.
| Workload | MiniMax M3.1 Flash | Llama 3 8B Lunaris |
|---|---|---|
| Support chatbot 1.2K in / 400 out × 200K requests | $37.14/mo | $13.60/mo |
| RAG assistant 8K in / 600 out × 100K requests | $51.00/mo | $35.00/mo |
| Coding agent 40K in / 4K out × 20K requests | $46.20/mo | $36.00/mo |
| Document extraction 20K in / 1.5K out × 50K requests | $94.13/mo | $43.75/mo |
| Bulk classification 500 in / 20 out × 5M requests | $183.75/mo | $105.00/mo |
Which should you pick?
You need to fit large documents in one call
MiniMax M3.1 Flash
Wider context window — 1.0M against 8K.
You are cost-constrained
Llama 3 8B Lunaris
Cheaper on blended list price at $0.042 per million tokens.
MiniMax M3.1 Flash vs Llama 3 8B Lunaris FAQ
Which is better, MiniMax M3.1 Flash or Llama 3 8B Lunaris?
Llama 3 8B Lunaris is the cheaper of the two; neither can be ranked on quality here. Llama 3 8B Lunaris does not have a published LiveBench run, so this comparison covers price, context and declared capabilities only. A missing score means "not evaluated", not "worse" — the right way to separate these two is an eval on your own workload.
Is MiniMax M3.1 Flash cheaper than Llama 3 8B Lunaris?
Llama 3 8B Lunaris is cheaper. On a 3:1 input:output blend, MiniMax M3.1 Flash lists at $0.131 per million tokens and Llama 3 8B Lunaris at $0.042 — Llama 3 8B Lunaris is 3.1× cheaper. Input and output are priced separately — MiniMax M3.1 Flash charges $0.075 in and $0.300 out, Llama 3 8B Lunaris charges $0.040 and $0.050 — so the model that looks cheaper flips depending on how output-heavy your workload is.
Does MiniMax M3.1 Flash or Llama 3 8B Lunaris have a bigger context window?
MiniMax M3.1 Flash has the larger context window: 1.0M for MiniMax M3.1 Flash against 8K for Llama 3 8B Lunaris. Note that a window you can fill is not a window you should fill — retrieval quality usually degrades well before the limit, and you pay for every token you put in it.
Do MiniMax M3.1 Flash and Llama 3 8B Lunaris support prompt caching?
MiniMax M3.1 Flash publishes a cached-input rate of $0.0075 per million tokens against a full input rate of $0.075. The catalogue lists no separate cached rate for Llama 3 8B Lunaris, which means the provider does not price it separately here — not that caching is unavailable.
Related comparisons
How these numbers are produced
- Price — provider list price from OpenRouter, refreshed every 15 minutes. “Blended” is a 3:1 input:output mix.
- Scores — LiveBench release 2026-10-25, using their own category map. Each model shows its strongest published run. A blank means “not evaluated”, never “bad”.
- Cost per point — the measured dollars LiveBench spent on the run, divided by the score it earned.
- “Win” — awarded only past a threshold: one full point on a benchmark score, 10% on a price, 25% on a context window. Anything tighter reports as a tie, because effort settings alone move a LiveBench score by more than that.
Published benchmarks rank models on someone else's tasks. Before committing, see LLM & agent evaluation for building an eval on your own.