Qwen3 32B API pricing

9 providers serve Qwen3 32B. Qwen3 32B is an open-weight model (Apache-2.0) with 32.8B total parameters, up to 131K context. Prices below are per 1M tokens, cheapest input first (self-hosting math further down).

Refreshed 2026-08-23 · list prices from provider APIs
Input floor $0.050/1M at Lambda Output floor $0.100/1M at Lambda Find your workload winner →
Provider Input $/1M Output $/1M Cache read $/1M Context
Lambda $0.050 $0.100output floor - 131K Use
OVHcloud $0.080 $0.230 - 32K Use
OpenRouter marketplace quote $0.080 $0.280 - 131K Use
DeepInfra $0.100 $0.280 - 41K Use
Nebius $0.100 $0.300 - 33K Use
Novita AI $0.100 $0.450 - 41K Use
Groq $0.290 $0.590 - 131K Use
SambaNova $0.400 $0.800 - 8K Use
Fireworks AI $0.900 $0.900 - 131K Use

The cheapest way to run Qwen3 32B

On an illustrative 70M-input / 30M-output monthly workload, today's lowest listed cost is roughly $6.50/month, at Lambda. 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 ~$0.290/1M. 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: Qwen3 32B self-hosting economics

Qwen3 32B is open-weight (Apache-2.0), so the API price above competes with the GPU-hour market. 32.8B total parameters needs roughly 46 GB VRAM at FP8 or 23 GB at INT4, KV-cache headroom included.

GPU that fits (FP8, single card)VRAMFrom $/hrCheapest at
A6000 48 GB $0.287marketplace Vast.ai Rent
A40 48 GB $0.350community RunPod Rent
6000 Ada 48 GB $0.388marketplace Vast.ai Rent
L40 48 GB $0.402marketplace Vast.ai Rent
A100 PCIe 80 GB $0.442marketplace Vast.ai Rent
L40S 48 GB $0.467marketplace Vast.ai Rent
Breakeven estimate: a well-batched vLLM deployment on one A6000 ($0.287/hr) at ~549 aggregate tok/s and 50% utilization works out to roughly $0.290 per 1M output tokens, versus $0.100 via the cheapest output-token API (Lambda). 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
Qwen3 235B A22B $0.071 $0.100 10
Qwen3 30B A3B $0.051 $0.200 7
Qwen3 Next 80B A3B Instruct $0.100 $0.900 7
Qwen3 Next 80B A3B Thinking $0.140 $0.900 7
Qwen3-Coder-480b-A35b-Instruct $0.220 $1.30 6
Qwen3 VL 235B A22B Instruct $0.210 $0.880 5

FAQ

What is the cheapest API for Qwen3 32B?

As of 2026-08-23, the lowest input price for Qwen3 32B is Lambda at $0.050 per 1M input tokens. The lowest output price is Lambda at $0.100 per 1M output tokens. The cheapest provider for a real workload depends on its input/output mix. The next-lowest input price is OVHcloud at $0.080, a 60% difference.

How much VRAM do you need to self-host Qwen3 32B?

Qwen3 32B has 32.8B parameters, so plan for roughly 46 GB of VRAM at FP8 or 23 GB at INT4/AWQ, KV-cache headroom included. A single A6000 (48 GB) fits it.

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