AI model comparison

GPT-5 mini vs Llama 3.1 70B

Comparing a managed small model with a hosted open-weight model for teams weighing vendor-managed simplicity against self-hostable flexibility.

Quick answer: GPT-5 mini lists the cheaper input ($0.25 vs $0.88 per 1M) while Llama 3.1 70B lists the cheaper output ($0.88 vs $2); the deeper difference is managed convenience versus open-weight portability.

Pricing & context

All figures below are list prices pulled directly from the Harpd pricing registry (last verified 2026-08-18). Prices change often — open each model’s source link to confirm before budgeting. Machine-readable copy: /data/llm-pricing.json.

MetricGPT-5 miniLlama 3.1 70B
ProviderOpenAIMeta · Together
Input / 1M tokens$0.25$0.88
Output / 1M tokens$2$0.88
Cached input / 1M tokens$0.03Not published
Batch discount50% offNot published
Context window400,000 tokens128,000 tokens
SourceOpenAI pricing ↗Meta · Together pricing ↗
GPT-5 mini lists the lower cost for this workload.

$325 vs $528 / month (100k calls, 5k in / 1k out)

Last updated
Methodology
Computed from list prices per 1M tokens; excludes prompt caching and batch discounts.
GPT-5 mini lists the larger context window.

400,000 tokens

Last updated
Harpd has not measured these two models head-to-head yet.

First benchmark: JSON extraction, 100 real tasks — target ship 2026-09-15

Last updated
Methodology
Until then, no performance win is claimed on this page — validate both models on your own tasks.
GPT-5 mini

Capabilities

GPT-5 mini is a managed, low-latency small model with a 400k context window, prompt caching, and a very low per-token price.

Best for

Turnkey high-volume workloads where no one on the team wants to run inference infrastructure, with a 400k window as a bonus.

Limitations

Managed-only: you cannot self-host it, $2 per 1M output costs 2.3× Llama's resale rate, and the 400k window beats Llama's 128k but locks you to one vendor.

Llama 3.1 70B

Capabilities

Llama 3.1 70B is an open-weight model available via resale hosting (Together AI, $0.88/$0.88 per 1M) with a 128k context window, offering flexibility for self-hosting or custom deployment.

Best for

Teams that need open-weight portability, on-prem or self-hosted deployment, or flat output pricing for generation-heavy volume.

Limitations

128k context is the smaller window of this pair, and resale prices move with the host — verify the Together AI page before budgeting.

Recommendation

The decision is less about raw quality and more about control versus convenience: GPT-5 mini is turnkey and cheap on input, while Llama 3.1 70B appeals when you want open-weight portability or on-prem options. Either can work for many tasks, but only testing on your real workload reveals which meets your bar. Compare both on your own representative tasks before committing.

Updated 2026-08-18. Sources: OpenAI and Meta · Together official pricing pages (verified 2026-08-18); no Harpd-measured benchmark yet.

Methodology & sources

Prices on this page come from the Harpd pricing registry, which mirrors the officialOpenAI and Meta · Together pricing pages and was last verified 2026-08-18. Capability notes summarize documented provider positioning — they are not Harpd measurements. Cheaper-cost claims are computed from the registry at a fixed reference workload, so they are reproducible from the published dataset. Read the pricing methodology and themodel replacement guide before switching a production workload.

Answer

Price tells you what a model costs. It does not tell you whether it can replace your current model on your real tasks.

Read the evaluation guide
Evidence

Related comparisons

Claude Haiku 4.5 vs GPT-5 miniGPT-5 mini lists the lower prices ($0.25/$2 per 1M versus $1/$5) and the larger context window (400k versus 200k); Claude Haiku 4.5 is positioned as the quality-stronger small tier at a higher list price.Mistral Large 3 vs Llama 3.1 70BLlama 3.1 70B (hosted on Together) lists far lower per-token prices ($0.88 flat vs $2/$6 per 1M), while Mistral Large 3 offers a managed flagship with multilingual positioning and European hosting options.

Explore related tools

Model Compare

Side-by-side pricing and capability explorer for every model in the registry.

LLM Pricing

Full list-price table across providers, updated from official sources.

Benchmarks

Open benchmark data — methodology, datasets and published results.

GPT-5 mini vs Llama 3.1 70B, answered

Which is cheaper, GPT-5 mini or Llama 3.1 70B?
GPT-5 mini lists the lower cost at Harpd's reference workload (100,000 calls/month, 5,000 input / 1,000 output tokens): about $325 versus $528 per month at list prices (0.25/2 vs 0.88/0.88 USD per 1M input/output tokens). The mix matters: if your workload is output-heavy, recompute with the model compare calculator.
What is the main difference between GPT-5 mini and Llama 3.1 70B?
GPT-5 mini lists the cheaper input ($0.25 vs $0.88 per 1M) while Llama 3.1 70B lists the cheaper output ($0.88 vs $2); the deeper difference is managed convenience versus open-weight portability.
Which has the larger context window?
GPT-5 mini lists 400,000 tokens versus 128,000 for Llama 3.1 70B, according to the Harpd pricing registry (last verified 2026-08-18).
Can I self-host either model?
Only Llama 3.1 70B. It ships open weights, so you can self-host it or move between hosts; the $0.88/$0.88 shown here is Together AI's resale price. GPT-5 mini is available only through OpenAI's managed API.
Which should I choose?
The decision is less about raw quality and more about control versus convenience: GPT-5 mini is turnkey and cheap on input, while Llama 3.1 70B appeals when you want open-weight portability or on-prem options. Either can work for many tasks, but only testing on your real workload reveals which meets your bar. Compare both on your own representative tasks before committing.