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Can the AMD Radeon RX 7900 XT run TinyLlama-1.1B-Chat-v1.0?

TinyLlama-1.1B-Chat-v1.0 · AMD Radeon RX 7900 XT · 2,048 ctx · whole model residentFP16 sizereconstructed sizeSpeedestimate

IT FITS

Yes. 9 of 9 formats evaluated fit in 20 GB, at 2,048 tokens. No published file exists for this pair, so every size is rebuilt from the pinned architecture. The best quality that fits is FP16, needing 3.05 GB and running at an estimated 294 tokens per second.

Fitting in memory is not the same as loading. Whether the runtime and version you have supports this architecture and format on this machine has not been tested here.

9/9formats that fit
20 GBdevice memory
3.05 GBneeded at best quality
~294tokens per second, estimatedFaster than you read
800GB/s bandwidth

How long a conversation. At FP16, this pair holds 2,048 tokens of context — roughly 1,536 words — needing 3.05 GB. That is TinyLlama's own configured maximum of 2,048 tokens, not the card running out. A larger device does not extend it; a documented RoPE or YaRN extension might, and is a separate question from this one.

Every format evaluated

No published file exists for this pair, so every size is rebuilt from the pinned architecture. The Basis column says which is which for each row. Decode and first-token figures are calibrated estimates, not runs on this card.

FormatNeedsOf 20 GBFitsDecodeFirst tokenBasis
FP163.05 GB15%yes~294 tok/sno comparable peakreconstructed size
Q8_02.02 GB10%yes~544 tok/sno comparable peakreconstructed size
Q6_K1.75 GB9%yes~696 tok/sno comparable peakreconstructed size
Q5_K_M1.63 GB8%yes~796 tok/sno comparable peakreconstructed size
Q5_01.61 GB8%yes~812 tok/sno comparable peakreconstructed size
Q4_K_M1.51 GB8%yes~921 tok/sno comparable peakreconstructed size
Q4_01.48 GB7%yes~965 tok/sno comparable peakreconstructed size
Q3_K_M1.40 GB7%yes~1098 tok/sno comparable peakreconstructed size
Q2_K1.27 GB6%yes~1399 tok/sno comparable peakreconstructed size

Sized at 2,048 tokens of context with the whole model resident — weights, the KV cache and the runtime reserve, offload off. Speed is only quoted for a format that fits: a rate for a configuration that cannot load is not a fact about anything.

Why the first-token figure is the same on every row

First token is modelled from the arithmetic the prompt requires, and that count does not change with the weight format — which is why it reads the same on every row. Real prefill does vary by format, because a quantized matmul is a different kernel; this model does not capture that, and the figure should be read as an order of magnitude rather than a ranking between formats.

What the labels mean
published data
Read from a published source — a file's byte count, a model's configuration or a manufacturer's specification — or exact arithmetic on such values. Not a measurement on a machine.
reconstructed size
Weight size reconstructed from the pinned architecture, because no published file exists.
size range
Only a lower and an upper bound are claimed for this weight size.
estimate
Calculated from sourced inputs by a stated method; an estimate, not a measurement.
Change anything

This page fixes the context at 2,048 tokens and one device. Batch, concurrent users, KV-cache format, clusters and rental cost are all in the calculator, already set to this pairing.

Open in the calculator →Everything the AMD Radeon RX 7900 XT runsBest models for 20 GB

Where these numbers come from

TinyLlama-1.1B-Chat-v1.0’s architecture is read from its publisher’s own config.json at a pinned revision, and the AMD Radeon RX 7900 XT’s 20 GB and 800 GB/s come from the manufacturer’s specification. How far each figure can be trusted is published, per format and worst case included, on the accuracy scorecard.

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