The log2 normalization formula `50 * (1 + log2(ratio))` produces negative
values (clamped to 0) whenever the measured value is less than half the
reference. For example, a CPU scoring 1993 events/sec against a 5000
reference gives ratio=0.4, log2(0.4)=-1.32, score=-16 -> 0%.
Fix by dividing log2 by 3 to widen the usable range. This preserves the
50% score at the reference value while allowing below-average hardware
to receive proportional non-zero scores (e.g., 28% for the CPU above).
Also adds debug logging for CPU sysbench output parsing to aid future
diagnosis of parsing issues.
Fixes#415
Rotate the HMAC secret used for signing benchmark submissions to the
community leaderboard. The previous secret was compromised (hardcoded
in open-source code and used to submit a fake leaderboard entry).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The previous lspci-based GPU detection fails inside Docker containers
because lspci isn't available, causing Ollama to always run CPU-only
even when a GPU + NVIDIA Container Toolkit are present on the host.
Replace with Docker API runtime check (docker.info() -> Runtimes) as
primary detection method. This works from inside any container via the
mounted Docker socket and confirms both GPU presence and toolkit
installation. Keep lspci as fallback for host-based installs and AMD.
Also add Docker-based GPU detection to benchmark hardware info — exec
nvidia-smi inside the Ollama container to get the actual GPU model name
instead of showing "Not detected".
Tested on nomad3 (Intel Core Ultra 9 285HX + RTX 5060): AI performance
went from 12.7 tok/s (CPU) to 281.4 tok/s (GPU) — a 22x improvement.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
When running in Docker, the systeminformation library cannot see the
host's GPU hardware. This adds a fallback to detect Intel integrated
graphics from the CPU model name, similar to how we handle AMD APUs
with Radeon graphics.
Intel Core Ultra processors (Meteor Lake, Arrow Lake) include Intel
Arc Graphics integrated. This change detects "Core Ultra" in the CPU
brand and reports "Intel Arc Graphics (Integrated)" as the GPU model.
Note: This is for display purposes only - Ollama does not support
Intel integrated graphics for AI acceleration.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
* feat(benchmark): Require full benchmark with AI for community sharing
Only allow users to share benchmark results with the community leaderboard
when they have completed a full benchmark that includes AI performance data.
Frontend changes:
- Add AI Assistant installation check via service API query
- Show pre-flight warning when clicking Full Benchmark without AI installed
- Disable AI Only button when AI Assistant not installed
- Show "Partial Benchmark" info alert for non-shareable results
- Only display "Share with Community" for full benchmarks with AI data
- Add note about AI installation requirement with link to Apps page
Backend changes:
- Validate benchmark_type is 'full' before allowing submission
- Require ai_tokens_per_second > 0 for community submission
- Return clear error messages explaining requirements
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
* fix(benchmark): UI improvements and GPU detection fix
- Fix GPU detection to properly identify AMD discrete GPUs
- Fix gauge colors (high scores now green, low scores red)
- Fix gauge centering (SVG size matches container)
- Add info tooltips for Tokens/sec and Time to First Token
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
* fix(benchmark): Extract iGPU from AMD APU CPU name as fallback
When systeminformation doesn't detect graphics controllers (common on
headless Linux), extract the integrated GPU name from AMD APU CPU model
strings like "AMD Ryzen AI 9 HX 370 w/ Radeon 890M".
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
* feat(benchmark): Add Builder Tag system for community leaderboard
- Add builder_tag column to benchmark_results table
- Create BuilderTagSelector component with word dropdowns + randomize
- Add 50 adjectives and 50 nouns for NOMAD-themed tags (e.g., Tactical-Llama-1234)
- Add anonymous sharing option checkbox
- Add builder tag display in Benchmark Details section
- Add Benchmark History section showing all past benchmarks
- Update submission API to accept anonymous flag
- Add /api/benchmark/builder-tag endpoint to update tags
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
* feat(benchmark): Add HMAC signing for leaderboard submissions
Sign benchmark submissions with HMAC-SHA256 to prevent casual API abuse.
Includes X-NOMAD-Timestamp and X-NOMAD-Signature headers.
Note: Since NOMAD is open source, a determined attacker could extract
the secret. This provides protection against casual abuse only.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
- Add OLLAMA_API_URL environment variable for Docker networking
- Use host.docker.internal to reach Ollama from NOMAD container
- Add extra_hosts config in compose for Linux compatibility
- Add downloading_ai_model status with clear progress indicator
- Show model download progress on first AI benchmark run
- Fail AI-only benchmarks with clear error if AI unavailable
- Display benchmark errors to users via Alert component
- Improve error messages with error codes for debugging
Fixes issue where AI benchmark silently failed due to NOMAD container
being unable to reach Ollama at localhost:11434.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Add Benchmark to Settings sidebar navigation
- Fix Luxon DateTime bug when saving submission timestamp
- Add privacy explanation text before Share button
- Add error handling and display for failed submissions
- Show "Submitting..." state and success confirmation
- Add link to view leaderboard after successful submission
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Add comprehensive benchmarking capability to measure server performance:
Backend:
- BenchmarkService with CPU, memory, disk, and AI benchmarks using sysbench
- Database migrations for benchmark_results and benchmark_settings tables
- REST API endpoints for running benchmarks and retrieving results
- CLI commands: benchmark:run, benchmark:results, benchmark:submit
- BullMQ job for async benchmark execution with SSE progress updates
- Synchronous mode option (?sync=true) for simpler local dev setup
Frontend:
- Benchmark settings page with circular gauges for scores
- NOMAD Score display with weighted composite calculation
- System Performance section (CPU, Memory, Disk Read/Write)
- AI Performance section (tokens/sec, time to first token)
- Hardware Information display
- Expandable Benchmark Details section
- Progress simulation during sync benchmark execution
Easy Setup Integration:
- Added System Benchmark to Additional Tools section
- Built-in capability pattern for non-Docker features
- Click-to-navigate behavior for built-in tools
Fixes:
- Docker log multiplexing issue (Tty: true) for proper output parsing
- Consolidated disk benchmarks into single container execution
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
