> ## Documentation Index > Fetch the complete documentation index at: https://mintlify.com/AlexsJones/llmfit/llms.txt > Use this file to discover all available pages before exploring further. # info > Show detailed information about a specific model ## Synopsis ```bash theme={null} llmfit info ``` ## Description Displays comprehensive information about a specific model including specifications, hardware requirements, fit analysis, score breakdown, and download sources. If multiple models match the query, you'll be prompted to be more specific. ## Arguments Model name or partial name to look up. Case-insensitive. ## Options Output model information as JSON instead of formatted text. Override GPU VRAM size for fit analysis (e.g., "32G", "32000M", "1.5T"). Cap context length used for memory estimation (tokens). Must be >= 1. ## Usage Examples ### Basic Model Info ```bash theme={null} # Get details about Llama 3.3 70B llmfit info llama-3.3-70b # Partial name match llmfit info "llama 70b" ``` ### JSON Output ```bash theme={null} # Get model info as JSON llmfit info llama-3.3-70b --json # Process with jq llmfit info deepseek-v3 --json | jq '.models[0].score_components' ``` ### Test Different Configurations ```bash theme={null} # Check fit with 24GB VRAM llmfit info llama-3.1-70b --memory 24G # Check fit with 8K context limit llmfit info qwen-2.5-72b --max-context 8192 ``` ### Multiple Model Info ```bash theme={null} # Compare multiple models llmfit info llama-3.3-70b llmfit info qwen-2.5-72b llmfit info deepseek-v3 ``` ## Example Output ### Detailed Info ``` === llama-3.3-70b === Provider: Meta Parameters: 70B Quantization: 4bit Best Quant: 4bit Context Length: 131072 tokens Use Case: general Category: General Released: 2024-12-06 Runtime: MLX (baseline est. ~42.5 tok/s) Score Breakdown: Overall Score: 95.2 / 100 Quality: 95 Speed: 43 Fit: 100 Context: 100 Baseline Est. Speed: 42.5 tok/s Resource Requirements: Min VRAM: 36.4 GB Min RAM: 43.7 GB (CPU inference) Recommended RAM: 87.5 GB Fit Analysis: Status: ✓ Perfect Run Mode: GPU Memory Utilization: 68.2% (43.7 / 64.0 GB) GGUF Downloads: bartowski → https://huggingface.co/bartowski/Llama-3.3-70B-Instruct-GGUF Tip: llmfit download bartowski/Llama-3.3-70B-Instruct-GGUF --quant 4bit Notes: High-quality general-purpose model from Meta Excellent for chat, reasoning, and code generation Requires significant VRAM for full GPU inference ``` ### MoE Model Info ```bash theme={null} $ llmfit info deepseek-v3 ``` ``` === deepseek-v3 === Provider: DeepSeek Parameters: 671B Quantization: Q4_K_M Best Quant: Q4_K_M Context Length: 131072 tokens Use Case: reasoning Category: Reasoning Released: 2024-12-26 Runtime: llama.cpp (baseline est. ~28.3 tok/s) Score Breakdown: Overall Score: 92.1 / 100 Quality: 98 Speed: 28 Fit: 89 Context: 100 Baseline Est. Speed: 28.3 tok/s Resource Requirements: Min VRAM: 350.2 GB Min RAM: 420.2 GB (CPU inference) Recommended RAM: 840.5 GB MoE Architecture: Experts: 8 active / 256 total per token Active VRAM: 57.4 GB (vs 350.2 GB full model) Offloaded: 292.8 GB inactive experts in RAM Fit Analysis: Status: ✓ Good Run Mode: MoE Offload Memory Utilization: 89.7% (57.4 / 64.0 GB) GGUF Downloads: unsloth → https://huggingface.co/unsloth/DeepSeek-V3-GGUF Tip: llmfit download unsloth/DeepSeek-V3-GGUF --quant Q4_K_M Notes: Advanced reasoning model with MoE architecture Sparse activation allows running on modest hardware GPU handles active experts, RAM holds inactive experts ``` ### Multiple Matches ```bash theme={null} $ llmfit info llama ``` ``` Multiple models found. Please be more specific: - llama-3.3-70b - llama-3.1-405b - llama-3.1-70b - llama-3.1-8b - llama-3.2-3b - llama-3.2-1b - llama-3.2-11b-vision - llama-3.2-90b-vision ``` ### No Match ```bash theme={null} $ llmfit info nonexistent ``` ``` No model found matching 'nonexistent' ``` ### JSON Format ```bash theme={null} $ llmfit info llama-3.3-70b --json ``` ```json theme={null} { "system": { "total_ram_gb": 64.0, "available_ram_gb": 58.24, "cpu_cores": 16, "gpu_vram_gb": 64.0, "backend": "Metal" }, "models": [ { "name": "llama-3.3-70b", "provider": "Meta", "parameter_count": "70B", "params_b": 70.0, "context_length": 131072, "use_case": "general", "category": "General", "release_date": "2024-12-06", "is_moe": false, "fit_level": "perfect", "run_mode": "gpu", "score": 95.2, "score_components": { "quality": 95.0, "speed": 42.5, "fit": 100.0, "context": 100.0 }, "estimated_tps": 42.5, "runtime": "MLX", "runtime_label": "MLX", "best_quant": "4bit", "memory_required_gb": 43.68, "memory_available_gb": 64.0, "utilization_pct": 68.2, "notes": [ "High-quality general-purpose model", "Excellent for chat, reasoning, and code" ], "gguf_sources": [ { "provider": "bartowski", "repo": "bartowski/Llama-3.3-70B-Instruct-GGUF" } ] } ] } ``` ## Information Sections ### Model Specs * Provider, parameter count, quantization * Context window size * Use case and category * Release date ### Score Breakdown * Overall composite score (0-100) * Individual components: quality, speed, fit, context * Estimated tokens/second throughput ### Resource Requirements * Minimum VRAM for GPU inference * Minimum RAM for CPU inference * Recommended RAM for comfortable operation ### MoE Details (if applicable) * Expert configuration (active/total) * Active VRAM usage * Offloaded expert size ### Fit Analysis * Fit level (Perfect, Good, Marginal, Too Tight) * Run mode (GPU, MoE Offload, CPU Offload, CPU Only) * Memory utilization percentage ### Download Sources * HuggingFace GGUF repositories * Download command examples ## Related Commands * [search](/api/commands/search) - Find models by name * [fit](/api/commands/fit) - Show compatible models * [plan](/api/commands/plan) - Plan hardware requirements * [recommend](/api/commands/recommend) - Get top recommendations