chore: import upstream snapshot with attribution

models/deepseek/deepseek-chat.toml

@@ -0,0 +1,30 @@
+name = "DeepSeek Chat"
+description = "DeepSeek chat model for instruction following, coding, and analysis"
+family = "deepseek"
+release_date = "2025-12-01"
+last_updated = "2026-02-28"
+attachment = true
+reasoning = false
+temperature = true
+tool_call = true
+knowledge = "2025-09"
+open_weights = true
+
+[limit]
+context = 1_000_000
+output = 384_000
+
+[modalities]
+input = ["text"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/deepseek-ai/DeepSeek-V3.2"
+
+[[benchmarks]]
+name = "Aider Polyglot"
+score = 70.2
+metric = "percent correct"
+source = "https://aider.chat/docs/leaderboards/"
+date = "2025-10-03"

models/deepseek/deepseek-r1.toml

@@ -0,0 +1,51 @@
+name = "DeepSeek-R1"
+description = "Classic open reasoning model for transparent math, coding, and deliberate problem solving"
+family = "deepseek-thinking"
+release_date = "2025-01-20"
+last_updated = "2025-05-29"
+attachment = false
+reasoning = true
+temperature = true
+tool_call = true
+knowledge = "2024-07"
+open_weights = true
+
+[limit]
+context = 128_000
+output = 32_768
+
+[modalities]
+input = ["text"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/deepseek-ai/DeepSeek-R1"
+
+[[benchmarks]]
+name = "Aider Polyglot"
+score = 56.9
+metric = "percent correct"
+source = "https://aider.chat/docs/leaderboards/"
+date = "2025-01-20"
+
+[[benchmarks]]
+name = "Artificial Analysis Coding Index"
+score = 15.9
+metric = "index"
+source = "https://openrouter.ai/deepseek/deepseek-r1/benchmarks"
+date = "2026-03-11"
+
+[[benchmarks]]
+name = "SciCode"
+score = 35.7
+metric = "percent correct"
+source = "https://openrouter.ai/deepseek/deepseek-r1/benchmarks"
+date = "2026-03-11"
+
+[[benchmarks]]
+name = "Terminal-Bench Hard"
+score = 6.1
+metric = "success rate"
+source = "https://openrouter.ai/deepseek/deepseek-r1/benchmarks"
+date = "2026-03-11"

models/deepseek/deepseek-reasoner.toml

@@ -0,0 +1,30 @@
+name = "DeepSeek Reasoner"
+description = "DeepSeek reasoning model for multi-step analysis, math, coding, and tools"
+family = "deepseek-thinking"
+release_date = "2025-12-01"
+last_updated = "2026-02-28"
+attachment = true
+reasoning = true
+temperature = true
+tool_call = true
+knowledge = "2025-09"
+open_weights = true
+
+[limit]
+context = 1_000_000
+output = 384_000
+
+[modalities]
+input = ["text"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/deepseek-ai/DeepSeek-V3.2"
+
+[[benchmarks]]
+name = "Aider Polyglot"
+score = 74.2
+metric = "percent correct"
+source = "https://aider.chat/docs/leaderboards/"
+date = "2025-10-03"

models/deepseek/deepseek-v4-flash.toml

@@ -0,0 +1,30 @@
+name = "DeepSeek V4 Flash"
+description = "Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work"
+family = "deepseek-flash"
+release_date = "2026-04-24"
+last_updated = "2026-04-24"
+attachment = false
+reasoning = true
+temperature = true
+tool_call = true
+structured_output = true
+knowledge = "2025-05"
+open_weights = true
+
+[limit]
+context = 1_000_000
+output = 384_000
+
+[modalities]
+input = ["text"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash"
+
+[[benchmarks]]
+name = "SWE-Bench Verified"
+score = 79
+metric = "resolved"
+source = "https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash"

models/deepseek/deepseek-v4-pro.toml

@@ -0,0 +1,64 @@
+name = "DeepSeek V4 Pro"
+description = "Open MoE flagship with million-token context for coding and long agent runs"
+family = "deepseek-thinking"
+release_date = "2026-04-24"
+last_updated = "2026-04-24"
+attachment = false
+reasoning = true
+temperature = true
+tool_call = true
+structured_output = true
+knowledge = "2025-05"
+open_weights = true
+
+[limit]
+context = 1_000_000
+output = 384_000
+
+[modalities]
+input = ["text"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro"
+
+[[benchmarks]]
+name = "SWE-Bench Verified"
+score = 80.6
+metric = "resolved"
+source = "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro"
+
+[[benchmarks]]
+name = "Artificial Analysis Coding Agent Index"
+score = 50.1
+metric = "average pass@1"
+harness = "Claude Code"
+variant = "high"
+source = "https://artificialanalysis.ai/agents/coding-agents"
+
+[[benchmarks]]
+name = "SWE-Atlas Codebase QnA"
+score = 67.8
+metric = "pass@1"
+harness = "Claude Code"
+variant = "high"
+source = "https://artificialanalysis.ai/agents/coding-agents"
+
+[[benchmarks]]
+name = "SWE-Bench Pro"
+score = 18
+metric = "pass@1"
+harness = "Claude Code"
+variant = "high"
+dataset = "hard-aa"
+source = "https://artificialanalysis.ai/agents/coding-agents"
+
+[[benchmarks]]
+name = "Terminal-Bench"
+score = 64.7
+metric = "pass@1"
+harness = "Claude Code"
+variant = "high"
+version = "2.1"
+source = "https://artificialanalysis.ai/agents/coding-agents"