EthanLab Software Development · Product Management · Tech Reviews
Back to research notes

Strata Model Benchmarks: IQ2_XS, IQ3_XXS and IQ3_S Speed, Quality and RAM Usage

Nine-run Strata benchmarks on an RTX 5060 Ti 16GB and 64 GiB RAM, compared with the author’s PC, plus LiveCodeBench scores and measured memory usage.

On an i7-11700 with an RTX 5060 Ti 16GB and 64 GiB RAM, nine-run Decode medians were 65.55, 51.30 and 42.45 tokens/s for IQ2_XS, IQ3_XXS and IQ3_S respectively. This article compares all three across Prefill/Decode, individual runs, author results and estimated inference time, LiveCodeBench scores, download size, RAM usage and remaining capacity. The IQ2_XS speed tests use Swift 1.5; both IQ3 tests use original Qwen. Quality scores for original quantizations are identified separately.

Strata series: Model benchmarks · Performance formula · Upgrade costs and benefits

All three models: nine-run benchmark overview

The tables below and the author comparison use one consistent baseline: IQ2_XS/IQ3_XXS were tested on October 11, 2026 with Strata 0.1.41; IQ3_S was tested on October 15 with 0.1.43.1. Each model has nine nominal 32K Prefill runs and nine nominal 4K Decode runs, totaling 54 engine runs. The newer IQ3_XXS retest is reported separately and is not mixed into these medians.

Nine-run medians and minimum–maximum for all three models, tokens/s
Model Prefill median Prefill range Decode median Decode range
IQ2_XS (Swift 1.5) 1,622.10 1,600.68–1,627.45 65.55 61.08–66.93
IQ3_XXS 1,666.44 1,648.03–1,667.46 51.30 50.78–53.42
IQ3_S 1,626.96 1,581.32–1,641.58 42.45 41.07–43.03
Test conditions by model
Item IQ2_XS IQ3_XXS IQ3_S
Model variant Swift 1.5 Original Qwen Original Qwen
Test date 2026-10-11 2026-10-11 2026-10-15
Strata 0.1.41 0.1.41 0.1.43.1
NVIDIA driver 591.86 591.86 610.88
KV streaming On; resident 32,768 On; resident 32,768 Off; selected by setup based on RAM

All three use the same PC, saved substitute source-code prompts and token IDs—not the author’s unpublished original text. Nominal 32K/4K prompts contain 31,566/3,562 tokens; timed Prefill covers 31,565/3,561, with the final prompt token handled by the first Decode step. Each run generates 256 tokens greedily, with a 65,536-token context, INT8 KV, MTP spec 4 / min-p 0.5, automatic expert cache and Prefill, and a 1,500 MiB VRAM reserve.

HTTP and vision services were stopped during benchmarking. Each sample used a fresh engine process, no prompt-cache reuse, and no OS file-cache flush. Model loading is excluded from timing. Each older nine-run set combines the original three runs with six additional runs; IQ3_S has nine new runs. No slower samples were discarded. Row N means each model’s Nth run, not simultaneous or interleaved testing. Variant, KV and driver differences are listed above, so this comparison reflects actual configurations rather than isolating quantization alone.

Prefill / nominal 32K: all nine results, tokens/s
Run IQ2_XS (Swift 1.5) IQ3_XXS IQ3_S
1 1,600.68 1,648.03 1,626.22
2 1,619.99 1,652.45 1,581.32
3 1,620.37 1,667.16 1,603.99
4 1,623.67 1,666.63 1,626.96
5 1,622.78 1,667.46 1,621.56
6 1,627.45 1,667.13 1,637.45
7 1,622.76 1,665.17 1,641.58
8 1,607.08 1,666.44 1,637.69
9 1,622.10 1,664.15 1,639.34
Decode / nominal 4K: all nine results, tokens/s
Run IQ2_XS (Swift 1.5) IQ3_XXS IQ3_S
1 61.08 51.54 41.89
2 64.07 50.85 42.10
3 64.78 50.78 42.44
4 66.18 51.01 42.45
5 65.55 51.20 41.07
6 66.92 51.63 42.73
7 63.27 51.30 42.60
8 66.93 53.42 43.03
9 66.93 51.57 42.77

Version retests and data coverage

Version coverage: nine-run Prefill / Decode medians, tokens/s
Model 0.1.41 0.1.43.1 New-version speed change
IQ2_XS (Swift 1.5) 1,622.10 / 65.55 Not tested No matched version pair
IQ3_XXS 1,666.44 / 51.30 1,665.73 / 51.65 Prefill −0.04%; Decode +0.68%
IQ3_S Not tested 1,626.96 / 42.45 No matched version pair

Only IQ3_XXS has nine-run tests for both versions. Its 0.1.43.1 figures come from the valid October 13, 2026 retest; invalidated batches are excluded. Those individual results are retained below. The author comparison and v4 prediction formula continue to use the 0.1.41 IQ3_XXS baseline.

IQ3_XXS / 0.1.43.1: nine additional valid retest runs, tokens/s
Run Prefill / 32K Decode / 4K
1 1,672.80 51.65
2 1,672.26 51.65
3 1,665.73 51.23
4 1,667.96 51.50
5 1,642.28 51.75
6 1,655.38 51.24
7 1,655.48 51.77
8 1,669.69 52.43
9 1,655.81 51.77

Same-model comparison: local PC versus Strata author

Hardware configurations
Item Local PC Strata author
CPU Intel Core i7-11700 AMD Ryzen 5 7600
GPU RTX 5060 Ti 16GB RTX 5070 12GB
GPU link PCIe 4.0 ×8 PCIe 5.0 ×16
RAM 64GB DDR4-3200, dual channel 64GB DDR5-5200, channel configuration unconfirmed

Both IQ2_XS results use Swift 1.5; IQ3_XXS and IQ3_S use original Qwen on both PCs. Local IQ2_XS / IQ3_XXS figures retain the nine-run medians from October 11, 2026, on Strata 0.1.41. IQ3_S uses the October 15 nine-run medians on Strata 0.1.43.1. Each author result is a single measurement. Times below are calculated for 51,200 input + 4,096 output tokens.

Throughput (tokens/s) and calculated time (seconds)
Model / metric Local speed Author speed Author speed increase Local seconds Author seconds Author time saved
Swift IQ2_XS / Prefill 1,622.10 2,092.02 +29.0% 31.6 24.5 22.5%
Swift IQ2_XS / Decode 65.55 78.60 +19.9% 62.5 52.1 16.6%
Swift IQ2_XS / Total — — — 94.1 76.6 18.6%
Original IQ3_XXS / Prefill 1,666.44 1,745.16 +4.7% 30.7 29.3 4.5%
Original IQ3_XXS / Decode 51.30 61.64 +20.2% 79.8 66.5 16.8%
Original IQ3_XXS / Total — — — 110.6 95.8 13.4%
Original IQ3_S / Prefill 1,626.96 1,624.07 −0.2% 31.5 31.5 −0.2%
Original IQ3_S / Decode 42.45 53.30 +25.6% 96.5 76.8 20.4%
Original IQ3_S / Total — — — 128.0 108.4 15.3%

Time saved = 1 − author time / local time. Speed increase = author tokens/s / local tokens/s − 1. Both use unrounded values. These are calculated model inference times, not measured end-to-end coding-agent task times.

The author used Strata 0.1.26 with an English MTP vocabulary; the local tests used 0.1.41 / 0.1.43.1 with a CJK MTP vocabulary. Prompts, context and KV conditions also differed, so the gap cannot be attributed entirely to hardware or quantization. Locally, original IQ3_XXS Prefill was 2.7% faster and Decode 21.7% slower than Swift IQ2_XS, changing both the model variant and quantization. IQ3_S also differs in KV settings and driver version, as noted above. Negative author speed-increase or time-saved percentages mean the author’s result was slower.

ISTA quantization quality: LiveCodeBench v6

Variant mapping: the IQ2_XS score of 83.43 and 68.0 GB download below describe ISTA’s original quantization, not the Swift 1.5 model used in the speed tests above. IQ3_XXS and IQ3_S speed and quality results both refer to original quantizations. All three have scores, but Swift speed and original-model quality must not be presented as measurements of one identical model.

These are ISTA-DASLab evaluations of original-model quantizations; Swift 1.5 is excluded. Higher scores are better. Download sizes use decimal GB and are not runtime RAM usage.

LiveCodeBench v6 scores for Qwen3.8-Flash-Next quantizations
LiveCodeBench v6 scores. Click the image for full size; the vertical axis starts at 80 to show the differences.
Model download size and coding benchmark score
Variant Download size (GB) LiveCodeBench v6
Q2_0 66.4 81.14
IQ2_XS 68.0 83.43
IQ3_XXS 75.8 86.29
IQ3_S 83.6 86.86
Coder IQ1_M, 50% of experts pruned 58.4 86.28
Original BF16 baseline — 87.43

Moving from IQ3_XXS to IQ3_S adds 7.8 GB to the download and improves the score by 0.57 points. Coder is a separate expert-pruned variant, not simply a lower-precision quantization. The chart’s vertical axis begins at 80 to magnify differences. Coding-problem scores are not success rates for complete coding-agent tasks. Sources: ISTA original-model evaluations and the Coder model card.

How much of 64 GiB RAM remains?

This PC has 64.00 GiB installed and 63.84 GiB usable by Windows. All three models are compared against that same capacity. This section uses GiB throughout; approximate memory budgets are not precise measurements.

RAM budget and remaining capacity for all three models (GiB)
Item IQ2_XS IQ3_XXS IQ3_S
Installed capacity 64.00 64.00 64.00
Total usable by Windows 63.84 63.84 63.84
Expert weights in RAM, approximately 33.53 40.05 46.57
Estimated total model RAM 39.12 (official) 45.63 (official) 52.15 (article estimate)
Capacity remaining after estimate 24.72 18.20 11.69
Measured unload/reload increment, including vision Not measured 44.12 Not measured
Capacity remaining after measured increment Not measured 19.72 Not measured

The IQ2_XS/IQ3_XXS total estimates follow the official expert-weights-plus-overhead figures. There is no equivalent official total for IQ3_S: this article adds the same approximately 5.59 GiB overhead to its officially stated expert size, giving 52.15 GiB. This is an inference, not an IQ3_S measurement or a directly published official total. The official IQ2_XS figure describes the original quantization; it is only a capacity guide for the similar Swift 1.5 architecture, which was not measured separately. The official decimal-GB estimates are converted to GiB; two decimal places aid comparison and do not imply measurement precision.

Remaining capacity still includes memory already used by Windows and other applications; it is not currently free RAM. The 44.12 GiB IQ3_XXS figure is the whole-system unload/reload difference measured on October 13, 2026 with a 65,536-token context and vision enabled. Caching and background activity affect it; it is not exclusive process memory. Official estimates and measurements are separate calculations, not cumulative deductions. Differences use unrounded values.

Definitions: Strata RAM estimates and expert weights and capacity requirements. Download size, system RAM and VRAM are different quantities; the RAM+VRAM column in MODELS must not be treated as system RAM alone.

Choosing between the three models

Tradeoffs on this PC
Model Priority it serves Tradeoff
IQ2_XS Faster answer generation and more RAM for development tools Speed tests use Swift; original-model quality scores do not transfer directly
IQ3_XXS Balance of original-model quality and remaining RAM Slower generation; development tools still need memory headroom
IQ3_S Highest LiveCodeBench score among these original quantizations Slowest generation and least capacity left for other work on 64 GiB

Original IQ3_XXS gains 2.86 LiveCodeBench points over original IQ2_XS; IQ3_S adds another 0.57. On this PC, their Prefill rates are close; the larger differences are Decode speed and RAM budget. These scores measure coding problems, not the reliability or completion rate of long coding-agent tasks.

Benchmark sources

Discussion

Share your thoughts

Your email address will not be published.