Standard base model
Eval workspace defaultstandard
Default base model in the Attempts evaluation workspace for structured extraction and JSON tasks.
Tuning: SFT
[Models]
Open-weight models Attempts can evaluate, tune, and deploy for your task. Inference rates are indicative for planning; training and dedicated deployment are quoted in your scoped plan. Eligibility and licensing are confirmed before training.
13 models in catalog
standard
Default base model in the Attempts evaluation workspace for structured extraction and JSON tasks.
Tuning: SFT
minimax-m3.1-flash
Long-context multimodal model for document-heavy workflows at low inference cost.
Tuning: SFT · DPO
glm-5.3-flash
Fast vision-language model for forms, scans, and mixed text-image inputs.
Tuning: SFT
deepseek-v4.1-flash
Strong price-performance for coding, extraction, and agent-style tool loops.
Tuning: SFT · DPO
deepseek-v4.1-flash-1017
Updated checkpoint for teams standardizing on the latest DeepSeek flash release.
Tuning: SFT
glm-5.3
Higher-capacity GLM tier when flash models plateau on complex reasoning tasks.
Tuning: SFT · DPO · RL
kimi-k3
Frontier open model for difficult extraction, long documents, and multi-step tasks.
Tuning: SFT · DPO
qwen3-coder-480b-a35b-instruct
Large code model for repository-scale context and structured codegen deliverables.
Tuning: SFT
qwen3.8-flash-next-fp8
Efficient Qwen flash tier for high-volume classification and short-form generation.
Tuning: SFT
openai-gpt-oss-20b
Compact open-weight GPT-OSS checkpoint for cost-sensitive production workloads.
Tuning: SFT · DPO
nemotron-3-ultra-nvfp4
NVIDIA Nemotron family model for enterprise assistants and tool-use prototypes.
Tuning: SFT
mimo-v2.6-pro-rl
RL-ready vision model when reward signals and rollout evaluators are already defined.
Tuning: SFT · RL
ember-1
Premium multimodal model when quality targets exceed mid-tier flash options.
Tuning: SFT