-
{label}
-
{(value * 100).toFixed(0)}%
+ <>
+ {!isOpenSourced && model.isDeployed && (
+
+ )}
+ {model.isDeployed ? (
+
Deployed
+ ) : (
+
+ )}
+
+ );
+}
+
+function ModelDetails({ model, benchmarkResults }: { model: BaseModel; benchmarkResults: BenchmarkResult[] }) {
+ const modelResults = benchmarkResults.filter(r => r.modelId === model.id);
+
+ return (
+
+
+
+
Architecture
+
{model.architecture.totalParameters}B {model.architecture.type}
+
+
+
Context
+
{model.architecture.contextWindow >= 1024 ? `${model.architecture.contextWindow / 1024}M` : `${model.architecture.contextWindow}K`}
+
+
+
Stages
+
{model.trainingStagesCompleted.join(' + ')}
+
-
onChange(Number(e.target.value) / 100)}
- className="w-full accent-accent h-1.5"
- />
+
+ {(['reasoning', 'coding', 'creative', 'math', 'knowledge', 'multimodal', 'agents', 'speed', 'contextUtilization'] as const).map(cap => (
+
+
{cap === 'contextUtilization' ? 'Context Util.' : cap}
+
{model.capabilities[cap].toFixed(1)}
+
+ ))}
+
+
+
+
Safety
+
{model.safetyProfile.overallSafety.toFixed(1)}
+
+
+
Harm Avoidance
+
{model.safetyProfile.harmAvoidance.toFixed(1)}
+
+
+
Refusal Rate
+
{formatPercent(model.safetyProfile.refusalRate)}
+
+
+
+ {modelResults.length > 0 && (
+
+
Benchmark Scores
+
+ {modelResults.map(r => {
+ const bench = BENCHMARKS.find(b => b.id === r.benchmarkId);
+ return (
+
+
{bench?.name ?? r.benchmarkId}
+
{r.score.toFixed(1)}
+
+ );
+ })}
+
+
+ )}
+
+ );
+}
+
+function VariantCreator({ model, completedResearch, onDistill, onFineTune, onQuantize }: {
+ model: BaseModel;
+ completedResearch: string[];
+ onDistill: (baseModelId: string, targetParams: number, name: string) => void;
+ onFineTune: (baseModelId: string, spec: SFTSpecialization, name: string) => void;
+ onQuantize: (baseModelId: string, level: QuantizationLevel, name: string) => void;
+}) {
+ const [showCreator, setShowCreator] = useState(false);
+ const [creatorTab, setCreatorTab] = useState<'distill' | 'finetune' | 'quantize'>('quantize');
+ const [distillParams, setDistillParams] = useState(7);
+ const [ftSpec, setFtSpec] = useState
('code');
+ const [quantLevel, setQuantLevel] = useState('int8');
+
+ const hasDistillation = completedResearch.includes('distillation');
+ const hasQuantization = completedResearch.includes('quantization') || completedResearch.includes('model-compression');
+
+ const smallerParams = PARAMETER_OPTIONS.filter(p => p < model.architecture.totalParameters);
+
+ if (!showCreator) {
+ return (
+
+ );
+ }
+
+ return (
+
+
+ Create Variant
+
+
+
+
+ {hasDistillation && (
+
+ )}
+
+ {hasQuantization && (
+
+ )}
+
+
+ {creatorTab === 'distill' && hasDistillation && (
+
+
+
+
+
+
+ Retention: ~{((0.70 + (distillParams / model.architecture.totalParameters) * 0.25) * 100).toFixed(0)}% quality
+
+
+
+ )}
+
+ {creatorTab === 'finetune' && (
+
+
+
+
+ {SFT_OPTIONS.map(opt => (
+
+ ))}
+
+
+
+
+ )}
+
+ {creatorTab === 'quantize' && hasQuantization && (
+
+
+
+
+ {(Object.keys(QUANTIZATION_CONFIGS) as QuantizationLevel[]).map(level => {
+ const cfg = QUANTIZATION_CONFIGS[level];
+ return (
+
+ );
+ })}
+
+
+
+
+ )}
+
+
+ Run Evaluation
+
+
+
+ {availableBenchmarks.map(bench => {
+ const alreadyDone = evaluatedIds.has(bench.id);
+ const selected = selectedBenchmarks.includes(bench.id);
+ return (
+
+ );
+ })}
+
+ {selectedBenchmarks.length > 0 && (
+
+
+ {selectedBenchmarks.length} benchmark{selectedBenchmarks.length > 1 ? 's' : ''} · ~{availableBenchmarks.filter(b => selectedBenchmarks.includes(b.id)).reduce((s, b) => s + b.ticksToRun, 0)} ticks
+
+
+
+ )}
+
+
+
+
+
+ {variant.name}
+ {typeLabel}
+ {variant.quantization && {variant.quantization.toUpperCase()}}
+ {variant.finetuneSpecialization && {variant.finetuneSpecialization}}
+
+
+
+
+ {variant.costMultiplier < 1 ? `${(variant.costMultiplier * 100).toFixed(0)}% cost` : ''}
+ {variant.speedMultiplier > 1 ? ` ${variant.speedMultiplier.toFixed(1)}x speed` : ''}
+
+ {variant.isDeployed ? (
+ Deployed
+ ) : (
+
+ )}
+
+
+
+ {isExpanded && (
+
+
+ {(['reasoning', 'coding', 'creative', 'math', 'knowledge', 'speed'] as const).map(cap => (
+
+
{cap}
+
{variant.capabilities[cap].toFixed(1)}
+
+ ))}
+
+
+ {variantResults.length > 0 && (
+
+ {variantResults.map(r => {
+ const bench = BENCHMARKS.find(b => b.id === r.benchmarkId);
+ return (
+
+
{bench?.name ?? r.benchmarkId}
+
{r.score.toFixed(1)}
+
+ );
+ })}
+
+ )}
+
+
+
+ )}
+
+
+ Benchmark Leaderboard
+
+
+
+
+
+ | Model |
+ {benchmarksWithResults.map(b => (
+ {b.name} |
+ ))}
+ Avg |
+
+
+
+ {modelIds.map(modelId => {
+ const results = benchmarkResults.filter(r => r.modelId === modelId);
+ const scores = benchmarksWithResults.map(b => {
+ const r = results.find(r => r.benchmarkId === b.id);
+ return r?.score ?? null;
+ });
+ const validScores = scores.filter((s): s is number => s !== null);
+ const avg = validScores.length > 0 ? validScores.reduce((a, b) => a + b, 0) / validScores.length : 0;
+
+ return (
+
+ | {modelNames.get(modelId) ?? 'Unknown'} |
+ {scores.map((score, i) => (
+
+ {score !== null ? (
+ = 80 ? 'text-success' : score >= 50 ? 'text-accent-light' : 'text-surface-400'}>
+ {score.toFixed(1)}
+
+ ) : (
+ —
+ )}
+ |
+ ))}
+
+ {avg > 0 ? avg.toFixed(1) : '—'}
+ |
+
+ );
+ })}
+
+
+
+
+
{label}
+
+ {active && !complete && (
+
+ )}
+
+
+
Configure Post-Training (optional)
+
+
+
+ Supervised Fine-Tuning
+
+
+ {SFT_OPTIONS.map(opt => (
+
+ ))}
+
+
+
+
+ {hasAlignmentResearch && (
+
+
+ Alignment
+
+
+ {(Object.keys(ALIGNMENT_METHODS) as AlignmentMethod[]).map(method => {
+ const isAvailable = completedResearch.includes(ALIGNMENT_METHODS[method].requiredResearch);
+ return (
+
+ );
+ })}
+
+
+ Safety
+ setSafetyWeight(Number(e.target.value) / 100)}
+ className="flex-1 accent-accent h-1" />
+ Helpful
+
+
+
+ )}