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Llama 3.1 8B API pricing

13 providers serve Llama 3.1 8B. Llama 3.1 8B is an open-weight model (Llama 3.1 Community) with 8B total parameters, up to 131K context. Prices below are per 1M tokens, cheapest input first (self-hosting math further down).

Refreshed 2026-10-08 · list prices from provider APIs
Input floor $0.020/1M at Nebius and Novita AI Output floor $0.030/1M at Nscale Find your workload winner →
Provider Input $/1M Output $/1M Cache read $/1M Context
Nebius $0.020 $0.060 - 128K Use
Novita AI $0.020 $0.050 - 16K Use
DeepInfra $0.030 $0.050 - 131K Use
Nscale $0.030 $0.030output floor - - Use
Llamagate $0.030 $0.050 - 131K
Vercel AI Gateway $0.050 $0.080 - 131K Use
OpenRouter $0.050 $0.080 $0.025 131K Use
OVHcloud $0.100 $0.100 - 131K Use
Hyperbolic $0.120 $0.300 - 33K Use
Cloudflare $0.152 $0.287 - 32K Use
Perplexity $0.200 $0.200 - 131K Use
W&B Inference $0.220 $0.220 - 131K Use
Oracle OCI $0.720 $0.720 - 128K Use

The cheapest way to run Llama 3.1 8B

On an illustrative 70M-input / 30M-output monthly workload, today's lowest listed cost is roughly $2.90/month, at Novita AI. Input-heavy, output-heavy and cache-heavy workloads can produce different winners. Use the live mix calculator below rather than combining floors from two different providers. On output-token cost alone, the API floor remains below our self-hosting estimate of ~$0.036/1M. Details below. Run your own numbers in the breakeven calculator, or read the breakeven math.

Your actual monthly cost

Uses today's list prices

Cache read uses the listed cache rate where available; otherwise it falls back to normal input price. Batch, write-cache, volume and negotiated discounts are excluded.

Or run it yourself: Llama 3.1 8B self-hosting economics

Llama 3.1 8B is open-weight (Llama 3.1 Community), so the API price above competes with the GPU-hour market. 8B total parameters needs roughly 11 GB VRAM at FP8 or 6 GB at INT4, KV-cache headroom included.

GPU that fits (FP8, single card)VRAMFrom $/hrCheapest at
V100 32 GB $0.055marketplace Vast.ai Rent
RTX 3090 24 GB $0.121marketplace Vast.ai Rent
RTX 4090 24 GB $0.136marketplace Vast.ai Rent
RTX A5000 24 GB $0.160community RunPod Rent
RTX A4000 16 GB $0.170community RunPod Rent
RTX 4000 SFF Ada Generation 20 GB $0.180community RunPod Rent
Breakeven estimate: a well-batched vLLM deployment on one V100 ($0.055/hr) at ~844 aggregate tok/s and 50% utilization works out to roughly $0.036 per 1M output tokens, versus $0.030 via the cheapest output-token API (Nscale). The API is cheaper unless your utilization or throughput beats these assumptions. Planning estimate: throughput varies with hardware, quantization, batch size and context. Tune it in the calculator.

Related models

ModelCheapest in $/1MCheapest out $/1MProviders
Llama 3.3 70B $0.120 $0.200 17
Llama 3.1 70B Instruct $0.120 $0.300 10
Llama 4 Scout $0.050 $0.100 9
Llama 3.2 3B $0.020 $0.020 9
Llama 4 Maverick $0.050 $0.100 8
Llama-3-70b $0.120 $0.300 7

FAQ

What is the cheapest API for Llama 3.1 8B?

As of 2026-10-08, the lowest input price for Llama 3.1 8B, $0.020 per 1M tokens, is the same list price at Nebius and Novita AI. The lowest output price is Nscale at $0.030 per 1M output tokens. The cheapest provider for a real workload depends on its input/output mix. The next-lowest input price is DeepInfra at $0.030, a 50% difference.

How much VRAM do you need to self-host Llama 3.1 8B?

Llama 3.1 8B has 8B parameters, so plan for roughly 11 GB of VRAM at FP8 or 6 GB at INT4/AWQ, KV-cache headroom included. A single V100 (32 GB) fits it.

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