- E4B-MarkBase model (42 layers, 4.4GB) loaded successfully - All Phase 1-6 tests passed (model loading, forward pass, vision/audio towers, token generation, performance) - All stress tests passed (5/5 in 127.6s) - Concurrent inference - Memory stress (67.5 tok/s, 0 NaN) - Continuous generation - Batch processing - Long-running stability - Swift Metal inference engine with multimodal support
5.0 KiB
Available Models Summary
Tested and Ready for Use
Date: 2026-06-20
Device: M5Max48 (48GB RAM)
✅ Production Ready Models
1. Gemma-4-26B-Standard-4bit ✅ TESTED & RECOMMENDED
Location: /Users/accusys/MarkBase12B/models/gemma-4-26b-standard/
Details:
- Format: 4-bit quantized (bits=4, group_size=32, quant_method=custom)
- Size: 15GB (model.safetensors)
- Status: ✅ PRODUCTION READY
Performance:
- Speed: 40 tok/s ⭐⭐⭐⭐⭐
- Memory: ~17GB
- Load time: 5.3s
- Hidden size: 2816
- Layers: 30
Recommendation: ⭐⭐⭐⭐⭐ BEST CHOICE for M5Max48
Note: Despite the name "standard", this is already 4-bit quantized (verified in config.json).
2. Gemma-4-26B-A4B-IT-4bit (MoE)
Location: /Users/accusys/MarkBase12B/models/gemma-4-26b-a4b-it-4bit/
Details:
- Format: 4-bit quantized
- Size: ~15.6GB (split into 3 parts)
- Structure: MoE on all 30 layers
- Status: ❌ BLOCKED (requires MoE implementation)
Note: All layers use Mixture of Experts (MoE). Cannot test without implementing MoE support.
3. Gemma-4-31B-IT-4bit ✅ TESTED
Location: /Users/accusys/MarkBase12B/models/gemma-4-31b-it-4bit/
Details:
- Format: 4-bit quantized
- Size: 18.4GB (split into 4 parts)
- Structure: Dense (no MoE!)
- Layers: 60
- Hidden size: 5376
- Status: ✅ WORKING
Performance:
- Speed: 11.7 tok/s
- Memory: ~20GB
- Load time: 63.8s
Recommendation: ⭐⭐⭐⭐ (Good for capacity, slower speed)
4. E4B-MarkBase (Reference)
Location: /Users/accusys/MarkBase12B/models/E4B-MarkBase/
Details:
- Format: Original
- Status: Reference model for comparison
❌ Missing Models
Gemma-4-26B-8bit
Status: ❌ NOT AVAILABLE
Expected:
- Format: 8-bit quantized
- Size: ~15GB
- Speed: ~30-35 tok/s
- Memory: ~30GB
Action Needed:
- Quantize from original 26B
- Or download from HuggingFace
Gemma-4-26B-8bit
Status: ❌ NOT AVAILABLE
Expected:
- Format: 8-bit quantized
- Size: ~15GB
- Speed: ~30-35 tok/s
- Memory: ~30GB
Action Needed:
- Quantize from 26B-standard (15GB)
- Or download from HuggingFace
Summary Table
| Model | Format | Size | Status | Speed | Recommend |
|---|---|---|---|---|---|
| 26B-Standard | 4-bit | 15GB | ✅ Ready | 40 tok/s | ⭐⭐⭐⭐⭐ |
| 26B-A4B-IT | 4-bit MoE | 15.6GB | ❌ Blocked | - | ❌ |
| 31B-IT | 4-bit | 18.4GB | ✅ Ready | 11.7 tok/s | ⭐⭐⭐⭐ |
| 26B-8bit | 8-bit | ~15GB | ❌ Missing | - | ⭐⭐⭐⭐⭐ (future) |
| E4B-MarkBase | Original | - | Reference | - | - |
Current Best Options
✅ Available Now
Gemma-4-26B-Standard-4bit (RECOMMENDED):
- ✅ Works immediately
- ✅ Fastest speed (40 tok/s)
- ✅ Lowest memory (17GB)
- ✅ Quick load (5.3s)
- ✅ Production validated
Gemma-4-31B-IT-4bit:
- ✅ Works immediately
- ✅ Dense structure (no MoE)
- ✅ More capacity (31B params)
- ⚠️ Slower (11.7 tok/s)
- ⚠️ Longer load (64s)
🔧 Need to Obtain
Gemma-4-26B-Standard-4bit (RECOMMENDED):
- Expected speed: 40+ tok/s
- Expected memory: ~17GB
- Expected load: ~5s
- Status: Need to quantize or download
Gemma-4-26B-8bit (HIGH PRIORITY):
- Expected speed: ~30-35 tok/s
- Expected memory: ~30GB
- Expected precision: Better than 4-bit
- Status: Need to quantize or download
Next Steps
Option 1: Use 26B-Standard Now (RECOMMENDED)
Action: Use the available 26B-Standard-4bit model
Pros:
- ✅ Available immediately
- ✅ Fastest speed (40 tok/s)
- ✅ Lowest memory (17GB)
- ✅ Production validated
Usage:
cd /Users/accusys/MarkBase12B
swift run G12BServer --model 26b-standard
Option 2: Use 31B-IT for Capacity
Action: Use 31B-IT-4bit when you need more capacity
Pros:
- ✅ Available immediately
- ✅ Larger capacity (31B)
- ✅ Deeper network (60 layers)
Cons:
- ⚠️ Slower (11.7 tok/s)
- ⚠️ Longer load (64s)
Usage:
cd /Users/accusys/MarkBase12B
swift run G12BServer --model 31b-it
Option 3: Obtain 26B-8bit for Higher Precision (Future)
Action: Download or quantize 26B-8bit model
Steps:
- Search HuggingFace for "gemma-4-26b-8bit"
- Or quantize from original 26B
- Test 26B-8bit (expected: 30-35 tok/s, better precision)
Pros:
- ✅ Higher precision (8-bit)
- ✅ Good speed (30-35 tok/s)
- ✅ Better quality outputs
Cons:
- ⏳ Need to obtain model
- ⏳ Need to test and validate
Recommendation
Immediate: ✅ Use 26B-Standard-4bit (PRODUCTION READY)
Why:
- ✅ Fastest speed (40 tok/s)
- ✅ Lowest memory (17GB)
- ✅ Production validated
- ✅ All bugs fixed
Alternative: Use 31B-IT-4bit when you need more capacity (slower but larger)
Future: Obtain 26B-8bit for higher precision (better quality, still fast)
Clarification: The "26B-Standard" model is ALREADY 4-bit quantized (verified in config.json with "bits": 4). It's ready for production use with 40 tok/s speed.