harn-vm 0.10.100

Async bytecode virtual machine for the Harn programming language
Documentation 
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# Baseten Model APIs. Live /v1/models re-verified 2026-08-15 with
# BASETEN_API_KEY: ids, served context windows, pricing, features, modalities,
# and route quantization come from the provider-owned endpoint. Rows are keyed
# with `baseten/<wire-id>` so failover/eval tooling can compare the same
# weights across Baseten, Z.AI, Together, DeepInfra, OpenRouter, and NVIDIA.
#
# The 2026-08-15 sweep POSTed a 5-token completion to every row rather than
# diffing the models listing, because a listed id is not necessarily a callable
# one. Four rows returned HTTP 410 "the model version you are trying to access
# has been deprecated" and were removed:
#
#   zai-org/GLM-5, zai-org/GLM-5.1  -- superseded by GLM-5.2 / GLM-5.2-Fast
#   moonshotai/Kimi-K2.5            -- superseded by Kimi-K2.6 / K2.7-Code
#   nvidia/Nemotron-120B-A12B       -- no successor at that size is served
#
# The same sweep found two context windows and one cache-read rate stale
# against the provider-owned metadata (GLM-5.2 was catalogued at 262144 tokens
# and $0.26/Mtok cache reads against a served 1048576 and $0.14; DeepSeek V4
# Pro at 131000 against a served 262144), so every surviving row below now
# carries the value the endpoint reports.

[models."baseten/zai-org/GLM-5.2"]
name = "GLM 5.2 (Baseten)"
provider = "baseten"
wire_model = "zai-org/GLM-5.2"
logical_model = "glm-5.2"
equivalence_group = "glm-5.2"
served_variant = "baseten-model-api"
api_dialect = "openai_chat"
context_window = 1048576
capabilities = ["tools", "streaming", "thinking", "prompt_caching"]
pricing = { input_per_mtok = 1.40, output_per_mtok = 4.40, cache_read_per_mtok = 0.14 }
architecture = { parameter_count_b = 744.0, active_parameter_count_b = 40.0, moe = true, quantization = "fp8", license = "MIT", source_url = "https://www.baseten.co/blog/how-we-built-the-worlds-fastest-api-for-glm-52/", last_verified = "2026-08-15" }
performance = { output_tokens_per_sec = 281.2, time_to_answer_s = 7.95, source = "artificial_analysis", source_url = "https://artificialanalysis.ai/models/glm-5-2/providers", last_verified = "2026-06-23", notes = "Artificial Analysis GLM-5.2 provider benchmark. The 2026-06-23 Harn probe that accompanied this figure also recorded native-tool unreliability; a 2026-08-15 re-probe found 16/16 clean native tool calls and that verdict was withdrawn." }
tier = "frontier"
open_weight = true
strengths = ["speed", "coding", "agentic", "tool_use", "reasoning", "long_context"]
complementary_with = ["anthropic-claude", "openai-gpt", "google-gemini", "kimi", "deepseek"]

# Same weights as the row above (Baseten reports `hugging_face_id
# zai-org/GLM-5.2` for both); the `-Fast` id is a higher-throughput serving
# tier priced at a 50% premium. Modelled the way `deepinfra-turbo` and
# `moonshot-direct-highspeed` are: one equivalence group, distinct
# served_variant.
[models."baseten/zai-org/GLM-5.2-Fast"]
name = "GLM 5.2 Fast (Baseten)"
provider = "baseten"
wire_model = "zai-org/GLM-5.2-Fast"
logical_model = "glm-5.2"
equivalence_group = "glm-5.2"
served_variant = "baseten-model-api-fast"
api_dialect = "openai_chat"
context_window = 1048576
capabilities = ["tools", "streaming", "thinking", "prompt_caching"]
pricing = { input_per_mtok = 2.10, output_per_mtok = 6.60, cache_read_per_mtok = 0.21 }
architecture = { parameter_count_b = 744.0, active_parameter_count_b = 40.0, moe = true, quantization = "fp8", license = "MIT", source_url = "https://www.baseten.co/blog/how-we-built-the-worlds-fastest-api-for-glm-52/", last_verified = "2026-08-15" }
tier = "frontier"
open_weight = true
strengths = ["speed", "coding", "agentic", "tool_use", "reasoning", "long_context"]
complementary_with = ["anthropic-claude", "openai-gpt", "google-gemini", "kimi", "deepseek"]

[models."baseten/moonshotai/Kimi-K2.7-Code"]
name = "Kimi K2.7 Code (Baseten)"
provider = "baseten"
wire_model = "moonshotai/Kimi-K2.7-Code"
logical_model = "moonshot-kimi-k2.7-code"
equivalence_group = "moonshot-kimi-k2.7-code"
served_variant = "baseten-model-api"
api_dialect = "openai_chat"
context_window = 262000
capabilities = ["tools", "vision", "streaming", "thinking", "prompt_caching"]
pricing = { input_per_mtok = 0.95, output_per_mtok = 4.00, cache_read_per_mtok = 0.16 }
architecture = { quantization = "fp4", source_url = "https://www.baseten.co/library/kimi-k27-code/", last_verified = "2026-08-15" }
tier = "frontier"
open_weight = true
strengths = ["coding", "agentic", "tool_use", "reasoning", "long_context", "vision"]
complementary_with = ["anthropic-claude", "openai-gpt", "google-gemini", "qwen", "deepseek"]

[models."baseten/deepseek-ai/DeepSeek-V4-Pro"]
name = "DeepSeek V4 Pro (Baseten)"
provider = "baseten"
wire_model = "deepseek-ai/DeepSeek-V4-Pro"
logical_model = "deepseek-v4-pro"
equivalence_group = "deepseek-v4-pro"
served_variant = "baseten-model-api"
api_dialect = "openai_chat"
context_window = 262144
capabilities = ["tools", "streaming", "thinking", "prompt_caching"]
pricing = { input_per_mtok = 1.74, output_per_mtok = 3.48, cache_read_per_mtok = 0.145 }
architecture = { parameter_count_b = 1600.0, active_parameter_count_b = 49.0, moe = true, quantization = "fp4", source_url = "https://www.baseten.co/library/deepseek-v4/", last_verified = "2026-08-15" }
tier = "frontier"
open_weight = true
strengths = ["reasoning", "coding", "agentic", "tool_use", "long_context"]
complementary_with = ["anthropic-claude", "openai-gpt", "google-gemini", "qwen", "kimi"]

# Dated snapshots. Baseten serves these alongside the undated ids, and they are
# the builds an eval should pin so a silent upstream reroute cannot change what
# a recorded trial measured.
[models."baseten/deepseek-ai/DeepSeek-V4-Pro-0813"]
name = "DeepSeek V4 Pro 0813 (Baseten)"
provider = "baseten"
wire_model = "deepseek-ai/DeepSeek-V4-Pro-0813"
logical_model = "deepseek-v4-pro-0813"
equivalence_group = "deepseek-v4-pro-0813"
served_variant = "baseten-model-api"
api_dialect = "openai_chat"
context_window = 1048576
capabilities = ["tools", "streaming", "thinking", "prompt_caching"]
pricing = { input_per_mtok = 1.32, output_per_mtok = 3.96, cache_read_per_mtok = 0.132 }
architecture = { parameter_count_b = 1600.0, active_parameter_count_b = 49.0, moe = true, quantization = "fp4", source_url = "https://www.baseten.co/library/deepseek-v4/", last_verified = "2026-08-15" }
tier = "frontier"
open_weight = true
strengths = ["reasoning", "coding", "agentic", "tool_use", "long_context"]
complementary_with = ["anthropic-claude", "openai-gpt", "google-gemini", "qwen", "kimi"]

[models."baseten/deepseek-ai/DeepSeek-V4-Flash-0731"]
name = "DeepSeek V4 Flash 0731 (Baseten)"
provider = "baseten"
wire_model = "deepseek-ai/DeepSeek-V4-Flash-0731"
logical_model = "deepseek-v4-flash-0731"
equivalence_group = "deepseek-v4-flash-0731"
served_variant = "baseten-model-api"
api_dialect = "openai_chat"
context_window = 1048576
capabilities = ["tools", "streaming", "thinking", "prompt_caching"]
pricing = { input_per_mtok = 0.13, output_per_mtok = 0.26, cache_read_per_mtok = 0.028 }
architecture = { parameter_count_b = 284.0, active_parameter_count_b = 13.0, moe = true, quantization = "fp8", source_url = "https://www.baseten.co/library/deepseek-v4/", last_verified = "2026-08-15" }
tier = "mid"
open_weight = true
strengths = ["speed", "cheap", "reasoning", "coding", "agentic", "tool_use", "long_context"]
complementary_with = ["anthropic-claude", "openai-gpt", "google-gemini", "qwen", "kimi"]

[models."baseten/nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B"]
name = "Nemotron 3 Ultra 550B A55B (Baseten)"
provider = "baseten"
wire_model = "nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B"
logical_model = "nemotron-3-ultra-550b-a55b"
equivalence_group = "nemotron-3-ultra-550b-a55b"
served_variant = "baseten-model-api"
api_dialect = "openai_chat"
context_window = 202800
capabilities = ["tools", "streaming", "thinking", "prompt_caching"]
pricing = { input_per_mtok = 0.60, output_per_mtok = 2.40, cache_read_per_mtok = 0.12 }
architecture = { parameter_count_b = 550.0, active_parameter_count_b = 55.0, moe = true, quantization = "fp4", source_url = "https://www.baseten.co/library/nemotron-3-ultra/", last_verified = "2026-08-15" }
tier = "frontier"
open_weight = true
strengths = ["reasoning", "coding", "agentic", "tool_use", "long_context"]
complementary_with = ["anthropic-claude", "openai-gpt", "google-gemini", "qwen", "deepseek", "kimi"]

[models."baseten/openai/gpt-oss-120b"]
name = "GPT-OSS 120B (Baseten)"
provider = "baseten"
wire_model = "openai/gpt-oss-120b"
logical_model = "openai-gpt-oss-120b"
equivalence_group = "openai-gpt-oss-120b"
served_variant = "baseten-model-api"
api_dialect = "openai_chat"
context_window = 128072
capabilities = ["tools", "streaming", "thinking", "prompt_caching"]
pricing = { input_per_mtok = 0.10, output_per_mtok = 0.50, cache_read_per_mtok = 0.10 }
architecture = { parameter_count_b = 117.0, active_parameter_count_b = 5.1, moe = true, quantization = "fp4", license = "Apache-2.0", source_url = "https://www.baseten.co/library/gpt-oss-120b/", last_verified = "2026-08-15" }
tier = "mid"
open_weight = true
strengths = ["cheap", "tool_use", "reasoning", "coding"]
complementary_with = ["anthropic-claude", "google-gemini", "qwen", "deepseek", "kimi"]

[models."baseten/zai-org/GLM-4.7"]
name = "GLM 4.7 (Baseten)"
provider = "baseten"
wire_model = "zai-org/GLM-4.7"
logical_model = "glm-4.7"
equivalence_group = "glm-4.7"
served_variant = "baseten-model-api"
api_dialect = "openai_chat"
context_window = 200000
capabilities = ["tools", "streaming", "prompt_caching"]
pricing = { input_per_mtok = 0.60, output_per_mtok = 2.20, cache_read_per_mtok = 0.12 }
architecture = { quantization = "fp4", source_url = "https://www.baseten.co/pricing/", last_verified = "2026-08-15" }
tier = "frontier"
open_weight = true
strengths = ["coding", "agentic", "tool_use", "long_context"]

[models."baseten/moonshotai/Kimi-K2.6"]
name = "Kimi K2.6 (Baseten)"
provider = "baseten"
wire_model = "moonshotai/Kimi-K2.6"
logical_model = "moonshot-kimi-k2.6"
equivalence_group = "moonshot-kimi-k2.6"
served_variant = "baseten-model-api"
api_dialect = "openai_chat"
context_window = 262000
capabilities = ["tools", "vision", "streaming", "thinking", "prompt_caching"]
pricing = { input_per_mtok = 0.95, output_per_mtok = 4.00, cache_read_per_mtok = 0.16 }
architecture = { quantization = "fp4", source_url = "https://www.baseten.co/pricing/", last_verified = "2026-08-15" }
tier = "frontier"
open_weight = true
strengths = ["coding", "agentic", "tool_use", "reasoning", "long_context", "vision"]