Google32 GB VRAM819 GB/s$0.8/hr

Qwen 3 4B on TPU v6e Trillium (32GB): Does It Fit, How Fast, What It Costs

Qwen 3 4B at FP16 needs 8.0 GB for its weights and 17.7 GB in total at 8K context with 8 concurrent users. That means it fits on a single TPU v6e Trillium (32GB). Every figure is computed by tokcalc's open-source capacity model.

Fits?
Yes, 1 GPU
17.7 GB needed / 32 GB available
Decode speed
66.54
tok/s per stream
Aggregate
798.5
tok/s @ 8 concurrent
Cost / 1M tokens
$0.2783
1× TPU v6e Trillium (32GB)
What changes as you add TPU v6e Trillium (32GB)s
Tensor-parallel degree vs VRAM, throughput, and cost. Cost scales linearly with GPU count; decode throughput scales near-linearly too, so cost per token stays roughly flat.
GPUsTotal VRAMVRAM neededDecode tok/sAggregate tok/sTTFTCost / 1M tokFits?
1× TPU32 GB17.7 GB66.54798.5187.8 ms$0.2783✓
2× TPU64 GB17.7 GB113.12715110.2 ms$0.1637✓
4× TPU128 GB17.7 GB226.21086070.1 ms$0.0819✓
8× TPU256 GB17.7 GB452.54344050.1 ms$0.0409✓
Concurrency vs context length
On 1× TPU v6e Trillium (32GB) at FP16. KV cache scales linearly with context, so this is the number of users your GPUs can actually serve.
ContextConcurrent usersKV per requestFits?
4K39618.5 MB✓ fits
8K191.21 GB✓ fits
33K44.83 GB✓ fits
66K29.66 GB✓ fits
131K119.33 GB✓ fits
Other GPUs that run Qwen 3 4B
Same workload, same quantization — ranked by value (tokens per dollar-hour).
GPUGPUsAggregate tok/sCost / 1M tok
RTX 3090 24GB1×912.6$0.0761
RTX 5090 32GB1×1747$0.0795
RTX 4090 24GB1×982.8$0.1131
AMD MI300X 192GB1×5168$0.1344
V100 SXM2 32GB1×877.5$0.1583
A100 40GB SXM41×1511$0.1654
Frequently asked questions

Can Qwen 3 4B run on TPU v6e Trillium (32GB)?

Yes. Qwen 3 4B at FP16 needs 17.7 GB including the KV cache, and TPU v6e Trillium (32GB) has 32 GB — so it fits on a single GPU.

How fast is Qwen 3 4B on TPU v6e Trillium (32GB)?

66.54 tokens/sec per stream and 798.5 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 187.8 ms, and inter-token latency is 15.0 ms.

What does Qwen 3 4B on TPU v6e Trillium (32GB) cost per million tokens?

$0.2783 per 1M output tokens at 1× TPU v6e Trillium (32GB) ($0.8000/hr). That is the marginal hardware cost — add idle capacity, ops, and egress for the real figure.

How much VRAM does Qwen 3 4B need on TPU v6e Trillium (32GB)?

8.0 GB for the weights at FP16, plus 9.7 GB of KV cache for 8 concurrent requests at 8K context — 17.7 GB total. Every extra concurrent user at long context costs more, so leave headroom.

Is TPU v6e Trillium (32GB) the right choice for Qwen 3 4B?

It works. Compare $0.2783 per 1M tokens against the alternatives below — the cheapest option that fits the same workload is 2× RTX 3080 10GB at $0.0441, and the fastest is 1× Cerebras CS-3 (WSE-3) at 19500 tok/s.

Adjust the workload yourself

Same formulas, your context length, concurrency, and quantisation.

Open in calculator