fanar-1-9b-instruct-fp8-msa
QCRI/Fanar-1-9B-Instruct quantized to FP8
via modelopt, calibrated on msa Arabic dialogue. Weights and activations are
quantized; this is a real packed checkpoint, not fake-quant.
Hardware: needs sm_89+ (Ada / Hopper / Blackwell) to run โ the most widely loadable of these.
Calibration
| set | calib1_msa.txt (msa) |
| dataset | Almheiri/ArabCulture-Dialogue |
| configs / split | KSA, UAE / eval |
| dataset revision | 9acd60cbbb4fab834b1054e9035499f035c5c0af |
| sampling seed | 1448 |
| samples | 128 dialogues, max 512 tokens |
| file digest | sha256[:16] = 19db9ec54d7ede9c |
Calibration is forward passes with observers attached โ no labels, no gradients, no generation. Observers record per-tensor absmax as data flows through. Weight scales are computed data-free from the weights themselves, so only the 294 activation ranges depend on this set.
Three sibling checkpoints exist per model and format โ -msa, -gulf and -mixed. They
differ only in calibration register: calib1_msa and calib2_gulf are line-parallel
(the same 128 dialogues in Modern Standard Arabic and in Gulf dialect), and calib3_mixed
is 128 distinct dialogues drawn from both. Any behavioural difference between them is
attributable to the calibration register and nothing else.
Quantization
| format | FP8 |
| backend | modelopt |
| weights | quantized |
| activations | quantized, 294 calibrated tensors |
| mean weight MSE, |W - Q(W)| | 3.034e-08 |
| weight quantizers | 294 |
| size | 17.57 GB -> 9.26 GB (1.90x smaller) |
| activation amax, min | 2.664 |
| activation amax, median | 40.906 |
| activation amax, max | 130.9 (model.layers.3.mlp.gate_proj) |
| max / median | 3x |
A large max/median amax ratio means a few tensors carry outliers far outside the typical range; those tensors dominate the activation quantization error.
Not benchmarked here
This checkpoint was produced by a build pipeline that computes no accuracy, perplexity, KL or agreement metrics. Do not read the numbers above as quality scores โ they describe the quantization, not the model's behaviour. Evaluation lives in the ArabicFP4 benchmark.
Note also that this is a W(4/8)A(4/8) checkpoint. The published ArabicFP4 benchmark measured weight-only simulated quantization with fp16 activations, so its accuracy deltas are a floor for what this costs, not a prediction.
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