engmauriciodias33
aura-fleet-gguf-part1
- Parameters
- 7.6B
- Max context length
- 32,768
- Architecture
- qwen2
About aura-fleet-gguf-part1
aura-fleet-gguf-part1 is a model published in GGUF format. GGUF files are published by engmauriciodias33/aura-fleet-gguf-part1. It has about 7.6B parameters, the qwen2 architecture, a maximum context length of 32,768 tokens (values written in the GGUF).
There is one quantization, Q4_K_M, with a file size of 4.68 GB (actual size on Hugging Face).
Running Q4_K_M (4.68 GB) with an 8,192-token context needs an estimated 6.23 GB of memory, and an estimated 7.64 GB at 32,768 tokens. For 8,192 tokens, a GPU with 6 GB or more of VRAM (such as Arc A380, GeForce RTX 4050 Laptop GPU), or a Mac with 6 GB or more of unified memory, is a rough guide (macOS caps how much memory the GPU can use, so leave some headroom).
File size and estimated memory per quantization
- Up to 8 GB
- Up to 16 GB
- Up to 24 GB
- Up to 48 GB
- Up to 128 GB
- More
File sizes are the actual values on Hugging Face. Memory is estimated for each context length (KV cache f16). The formula is in How memory is calculated.
All memory figures are Estimated (KV cache f16). It should run on a setup with at least this much VRAM (or Mac unified memory). Click a value to see the devices and models that fit that amount (Find by GPU / Mac).
About the "quality guide" (how far a quantization drifts from the original)
For each quantization type, how far the output drifts from the original model, grouped into six levels from values llama.cpp measured on Llama-3-8B.
The value is mean KLD (the difference between the original and quantized model in next-token probabilities); smaller means closer to the original. Quantizations made with an imatrix (importance data) come out slightly smaller. Levels use the value without an imatrix (or with one, for types that only have that).
These values were not measured on this model. Larger models and MoE models tend to drift less with the same type. Distributor-specific mixed types (such as UD-Q4_K_XL) cannot be matched by type name alone, so they show "-".
| Quantization | Quality guide | KLD (no imatrix) | KLD (imatrix) | Size (Llama-3-8B) |
|---|---|---|---|---|
| Q8_0 | Nearly identical | 0.0014 | - | 7.96 GiB |
| Q6_K | Very small | 0.0055 | - | 6.14 GiB |
| Q5_K_M | Very small | 0.0108 | - | 5.33 GiB |
| Q5_K_S | Small | 0.0166 | - | 5.21 GiB |
| Q5_1 | Small | 0.0180 | - | 5.65 GiB |
| Q5_0 | Small | 0.0222 | - | 5.21 GiB |
| Q4_K_M | Small | 0.0313 | 0.0282 | 4.58 GiB |
| Q4_K_S | Medium | 0.0431 | 0.0320 | 4.37 GiB |
| IQ4_NL | Small | - | 0.0357 | 4.35 GiB |
| IQ4_XS | Small | - | 0.0363 | 4.14 GiB |
| Q4_1 | Medium | 0.0717 | - | 4.78 GiB |
| Q4_0 | Medium | 0.0719 | - | 4.34 GiB |
| Q3_K_L | Medium | 0.0872 | 0.0731 | 4.03 GiB |
| Q3_K_M | Medium | 0.1019 | 0.0844 | 3.74 GiB |
| IQ3_M | Medium | - | 0.1025 | 3.53 GiB |
| IQ3_S | Medium | - | 0.1113 | 3.42 GiB |
| IQ3_XS | Large | - | 0.1387 | 3.28 GiB |
| IQ3_XXS | Large | - | 0.1836 | 3.05 GiB |
| Q3_K_S | Large | 0.2282 | 0.1998 | 3.41 GiB |
| IQ2_M | Large | - | 0.3260 | 2.74 GiB |
| Q2_K | Very large | 0.4451 | 0.3322 | 2.96 GiB |
| Q2_K_S | Very large | - | 0.4034 | 2.96 GiB |
| IQ2_S | Very large | - | 0.4392 | 2.56 GiB |
| IQ2_XS | Very large | - | 0.5463 | 2.43 GiB |
| IQ2_XXS | Very large | - | 0.8120 | 2.24 GiB |
| IQ1_M | Very large | - | 1.3931 | 2.01 GiB |
| IQ1_S | Very large | - | 2.2546 | 1.88 GiB |
Source: llama.cpp (MIT), measured on Llama-3-8B against FP16, Wikitext-2, revision f364eb6f. Original table · Reading and choosing quantizations
GGUF source
engmauriciodias33/aura-fleet-gguf-part1
Published by the original developer About this label
Last checked: Nov 2, 2026
- Architecture
- qwen2
- Supported before llama.cpp b4409
- Parameters
- 7.6B
- Max context length
- 32,768
| Quantization | File size Measured | Quality guide | 4,096 | 8,192 | 16,384 | 32,768 max |
|---|---|---|---|---|---|---|
| Q4_K_M aura_expert_370_metamaterial_acoustic_electromagnetic_cloak_multi_physics_coupling_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_390_metamaterial_acoustic_electromagnetic_cloak_omega_integration_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_398_solid_state_garnet_electrolyte_dendrite_free_omega_integration_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_386_hypersonic_scramjet_magnetohydrodynamic_omega_integration_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_922_sodium_sugar_hard_carbon_cathode_hardware_verilog_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_382_sodium_sugar_hard_carbon_cathode_omega_integration_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_925_aneutronic_boron_laser_ignition_hardware_verilog_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_379_orbital_tether_momentum_exchange_launcher_multi_physics_coupling_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_378_solid_state_garnet_electrolyte_dendrite_free_multi_physics_coupling_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_926_hypersonic_scramjet_magnetohydrodynamic_hardware_verilog_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_376_quantum_gravimetry_subterranean_mineral_mapper_multi_physics_coupling_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_373_room_temp_hydride_superconductor_wire_multi_physics_coupling_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_930_metamaterial_acoustic_electromagnetic_cloak_hardware_verilog_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_933_room_temp_hydride_superconductor_wire_hardware_verilog_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_936_quantum_gravimetry_subterranean_mineral_mapper_hardware_verilog_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_365_aneutronic_boron_laser_ignition_multi_physics_coupling_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_336_quantum_gravimetry_subterranean_mineral_mapper_materials_discovery_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_946_hypersonic_scramjet_magnetohydrodynamic_quantum_solver_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_350_metamaterial_acoustic_electromagnetic_cloak_high_frequency_dynamics_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_945_aneutronic_boron_laser_ignition_quantum_solver_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_353_room_temp_hydride_superconductor_wire_high_frequency_dynamics_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_942_sodium_sugar_hard_carbon_cathode_quantum_solver_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_356_quantum_gravimetry_subterranean_mineral_mapper_high_frequency_dynamics_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_939_orbital_tether_momentum_exchange_launcher_hardware_verilog_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_938_solid_state_garnet_electrolyte_dendrite_free_hardware_verilog_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_366_hypersonic_scramjet_magnetohydrodynamic_multi_physics_coupling_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_941_silicon_photonics_sub_angstrom_quantum_solver_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_927_autonomous_depin_byzantine_mesh_hardware_verilog_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_929_aya_64kb_progressive_tensor_pager_hardware_verilog_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_943_post_quantum_lattice_zk_rollup_quantum_solver_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_923_post_quantum_lattice_zk_rollup_hardware_verilog_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_921_silicon_photonics_sub_angstrom_hardware_verilog_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_387_autonomous_depin_byzantine_mesh_omega_integration_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_947_autonomous_depin_byzantine_mesh_quantum_solver_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_349_aya_64kb_progressive_tensor_pager_high_frequency_dynamics_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_383_post_quantum_lattice_zk_rollup_omega_integration_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_381_silicon_photonics_sub_angstrom_omega_integration_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_363_post_quantum_lattice_zk_rollup_multi_physics_coupling_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_367_autonomous_depin_byzantine_mesh_multi_physics_coupling_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_395_deep_sea_cobalt_crust_autonomous_harvester_omega_integration_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_335_deep_sea_cobalt_crust_autonomous_harvester_materials_discovery_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_352_riscv_formal_verified_microkernel_seL4_high_frequency_dynamics_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_354_bci_32ch_eegnet_motor_imagery_decoder_high_frequency_dynamics_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_355_deep_sea_cobalt_crust_autonomous_harvester_high_frequency_dynamics_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_935_deep_sea_cobalt_crust_autonomous_harvester_hardware_verilog_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_934_bci_32ch_eegnet_motor_imagery_decoder_hardware_verilog_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_932_riscv_formal_verified_microkernel_seL4_hardware_verilog_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_332_riscv_formal_verified_microkernel_seL4_materials_discovery_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_374_bci_32ch_eegnet_motor_imagery_decoder_multi_physics_coupling_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_375_deep_sea_cobalt_crust_autonomous_harvester_multi_physics_coupling_q4_k_m | 4.68 GB | Small | 5.99 GB | 6.23 GB | 6.70 GB | 7.64 GB |
| Q4_K_M aura_expert_377_mrna_neoantigen_personalized_oncology_multi_physics_coupling_q4_k_m | 4.92 GB | Small | 6.23 GB | 6.46 GB | 6.93 GB | 7.87 GB |
| Q4_K_M aura_expert_391_synthetic_cyanobacteria_co2_to_butanol_omega_integration_q4_k_m | 4.92 GB | Small | 6.23 GB | 6.46 GB | 6.93 GB | 7.87 GB |
| Q4_K_M aura_expert_351_synthetic_cyanobacteria_co2_to_butanol_high_frequency_dynamics_q4_k_m | 4.92 GB | Small | 6.23 GB | 6.46 GB | 6.93 GB | 7.87 GB |
| Q4_K_M aura_expert_944_crispr_epigenetic_methylation_reset_quantum_solver_q4_k_m | 4.92 GB | Small | 6.23 GB | 6.46 GB | 6.93 GB | 7.87 GB |
| Q4_K_M aura_expert_384_crispr_epigenetic_methylation_reset_omega_integration_q4_k_m | 4.92 GB | Small | 6.23 GB | 6.46 GB | 6.93 GB | 7.87 GB |
| Q4_K_M aura_expert_924_crispr_epigenetic_methylation_reset_hardware_verilog_q4_k_m | 4.92 GB | Small | 6.23 GB | 6.46 GB | 6.93 GB | 7.87 GB |
| Q4_K_M aura_expert_380_anti_lawfare_sovereign_jurisprudence_ai_multi_physics_coupling_q4_k_m | 4.92 GB | Small | 6.23 GB | 6.46 GB | 6.93 GB | 7.87 GB |
| Q4_K_M aura_expert_940_anti_lawfare_sovereign_jurisprudence_ai_hardware_verilog_q4_k_m | 4.92 GB | Small | 6.23 GB | 6.46 GB | 6.93 GB | 7.87 GB |
| Q4_K_M aura_expert_931_synthetic_cyanobacteria_co2_to_butanol_hardware_verilog_q4_k_m | 4.92 GB | Small | 6.23 GB | 6.46 GB | 6.93 GB | 7.87 GB |
| Q4_K_M aura_expert_364_crispr_epigenetic_methylation_reset_multi_physics_coupling_q4_k_m | 4.92 GB | Small | 6.23 GB | 6.46 GB | 6.93 GB | 7.87 GB |
| Q4_K_M aura_expert_937_mrna_neoantigen_personalized_oncology_hardware_verilog_q4_k_m | 4.92 GB | Small | 6.23 GB | 6.46 GB | 6.93 GB | 7.87 GB |
| Q4_K_M aura_expert_928_brics_commodity_clearing_smart_settlement_hardware_verilog_q4_k_m | 4.92 GB | Small | 6.23 GB | 6.46 GB | 6.93 GB | 7.87 GB |
| Q4_K_M aura_expert_368_brics_commodity_clearing_smart_settlement_multi_physics_coupling_q4_k_m | 4.92 GB | Small | 6.23 GB | 6.46 GB | 6.93 GB | 7.87 GB |
| Q4_K_M aura_expert_371_synthetic_cyanobacteria_co2_to_butanol_multi_physics_coupling_q4_k_m | 4.92 GB | Small | 6.23 GB | 6.46 GB | 6.93 GB | 7.87 GB |
Ollama ollama run hf.co/engmauriciodias33/aura-fleet-gguf-part1:Q4_K_M
llama.cpp llama-server -hf engmauriciodias33/aura-fleet-gguf-part1:Q4_K_M
Generation speed on common GPUs and Macs (estimated)
A rough guide to how fast Q4_K_M (4.68 GB) generates text. Each token reads the model weights once, so the upper limit is memory bandwidth ÷ file size. The guide is 60–80% of that, where most published measurements fall.
| Device | Memory bandwidth | Guide (tokens/s) Estimated | Upper limit |
|---|---|---|---|
| Arc A380 6 GB | 186 GB/s | 24–32 | 40 |
| Arc A770M 16 GB | 512 GB/s | 66–87 | 109 |
| GeForce RTX 5090 32 GB | 1,792 GB/s | 230–306 | 383 |
| Apple M2 8 GB | 100 GB/s | 13–17 | 21 |
| Apple M2 Pro 16 GB | 200 GB/s | 26–34 | 43 |
| Apple M5 Ultra 96 GB | 1,200 GB/s | 154–205 | 256 |
Estimates only. Prompt processing speed (limited by compute) is not included. Longer contexts and offloading part of the model to the CPU make it slower. Macs are shown only when installed memory is at least 4/3 of what is needed. Devices without published bandwidth (some GeForce cards, etc.) are not shown.
How to run
Example commands using Q4_K_M. To use another quantization, replace the name with one from the table above. How to run local LLMs
Ollama
Run it by pointing directly at the GGUF on Hugging Face.
ollama run hf.co/engmauriciodias33/aura-fleet-gguf-part1:Q4_K_M
llama.cpp
Pass the repository and quantization name to llama-server (or llama-cli) with -hf.
llama-server -hf engmauriciodias33/aura-fleet-gguf-part1:Q4_K_M
LM Studio
Paste engmauriciodias33/aura-fleet-gguf-part1 into the search box, download it, and choose the quantization from the file list.
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Measured Estimated VRAM 8 GB+
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Measured Estimated VRAM 8 GB+
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Frequently asked questions
- How much memory do I need to run aura-fleet-gguf-part1 (Q4_K_M)?
- The file size is 4.68 GB (measured). With a 8,192-token context, the estimated memory including the KV cache is 6.23 GB. The formula is published at https://localllm.az-arte.com/en/guide/memory-calculation.
- Does aura-fleet-gguf-part1 run in 8 GB, 12 GB, 16 GB or 24 GB of VRAM?
- 8 GB: up to Q4_K_M (est. 6.46 GB); 12 GB: up to Q4_K_M (est. 6.46 GB); 16 GB: up to Q4_K_M (est. 6.46 GB); 24 GB: up to Q4_K_M (est. 6.46 GB) (estimated at 8,192 tokens with an f16 KV cache, files from the most-downloaded source).
- What is the command to run aura-fleet-gguf-part1 with Ollama?
- Run "ollama run hf.co/engmauriciodias33/aura-fleet-gguf-part1:Q4_K_M" to use the GGUF on Hugging Face directly. To use another quantization, replace the name at the end.