--- a/Sources/MereRunCore/UnlimitedOCR/UnlimitedOCRGenerator.swift
+++ b/Sources/MereRunCore/UnlimitedOCR/UnlimitedOCRGenerator.swift
@@ -32,6 +32,18 @@
         progress: (@Sendable (String) -> Void)? = nil
     ) async throws -> Result {
         try await MLXRequestStreams.withStream(isolation: self) {
+            let capture = ProcessInfo.processInfo.environment["MERERUN_UNLIMITED_OCR_CAPTURE"].map { URL(fileURLWithPath: $0) }
+            if let capture { try FileManager.default.createDirectory(at: capture, withIntermediateDirectories: true) }
+            func saveCapture(_ name: String, _ array: MLXArray) throws {
+                if let capture { try MLX.save(arrays: [name: array], url: capture.appendingPathComponent(name + ".safetensors")) }
+            }
+            if let capture {
+                let env = ProcessInfo.processInfo.environment
+                let settings = ["device": String(describing: Device.defaultDevice()),
+                                "metallibOverride": GPU.metallib?.path ?? "none"]
+                    .merging(env.filter { $0.key.hasPrefix("MLX_") || $0.key.hasPrefix("MTL_") }) { first, _ in first }
+                try JSONEncoder().encode(settings).write(to: capture.appendingPathComponent("settings.json"))
+            }
             let window = ngramWindow ?? (imageURLs.count > 1 ? 1024 : 128)
             guard !imageURLs.isEmpty, maxTokens > 0, temperature.isFinite, temperature >= 0,
                   noRepeatNgramSize >= 0, window > 0 else {
@@ -50,11 +62,13 @@
             for (index, url) in imageURLs.enumerated() {
                 try Task.checkCancellation()
                 let page = try UnlimitedOCRImage.prepare(url, crop: crop ?? (imageURLs.count == 1))
+                try saveCapture("pixels.\(index)", page.global)
                 progress?("Encoding page \(index + 1)/\(imageURLs.count): \(page.tiles.count) tiles, \(page.tokenCount) visual tokens")
                 let marker = decoder.config.sparseAttentionConfig.pageTokenId
                 ids.append(marker)
                 pieces.append(decoder.embeddings([marker]))
                 let features = vision.page(global: page.global, tiles: page.tiles, columns: page.columns, rows: page.rows)
+                try saveCapture("features.\(index)", features)
                 guard features.dim(0) == page.tokenCount else { throw UnlimitedOCRError.invalidInput("Image token count mismatch.") }
                 pieces.append(features)
                 ids += [Int](repeating: decoder.config.sparseAttentionConfig.imageTokenId, count: page.tokenCount)
@@ -72,6 +86,7 @@
             let prefillStart = Date()
             var logits = decoder.forward(concatenated(pieces, axis: 0), state: state, cache: cache)
             eval(logits)
+            try saveCapture("prefill", logits)
             let prefillSeconds = Date().timeIntervalSince(prefillStart)
             progress?("Decoding")
             let decodeStart = Date()
@@ -94,6 +109,7 @@
                 }
                 let token = temperature == 0 ? argMax(logits).item(Int.self)
                     : MLXRandom.categorical(logits / temperature).item(Int.self)
+                if capture != nil && step < 2 { try saveCapture("decode.\(step)", logits) }
                 if token == eos { stopped = true; break }
                 output.append(token)
                 if output.count.isMultiple(of: 256) { progress?("Decoded \(output.count) tokens") }
@@ -104,6 +120,7 @@
                 }
                 if Memory.cacheMemory >= 1_073_741_824 { Memory.clearCache() }
             }
+            if let capture { try JSONEncoder().encode(output).write(to: capture.appendingPathComponent("tokens.json")) }
             return Result(text: tokenizer.decode(tokens: output, skipSpecialTokens: false),
                           tokensGenerated: output.count, pagesGenerated: pages, reachedTokenLimit: !stopped,
                           loadSeconds: loadSeconds, visionSeconds: visionSeconds, prefillSeconds: prefillSeconds,