Model reference · open weights
KDL-Frontier-Parser-nano is an open-weight language model from KDLAI. AxForge deploys and operates it for you on dedicated EU-owned hardware — with the licence handled where one is required.
Available as managed deployment — configured and operated for you on dedicated EU hardware, quoted per deployment.
What it is
| Released by | KDLAI |
|---|---|
| Type | Language models |
| Task | Vision + text |
| Parameters (lead) | 1.2B |
| Context | 8k tokens |
| Released | 2026-06-10 |
| Popularity | 12k downloads / month |
| Licence | Commercial licence needed |
About
A 1.2B-parameter open-weight document parsing model, packaged and orchestrated by KoreaDeep as the nano tier of the KDL Frontier Parser family.
Measured 2026-06-10 with the official ParseBench harness, full set, single end-to-end pass (2,553 test cases, 0 inference failures):
| Dimension | Metric | Score |
|---|---|---|
| Overall (mean) | mean of 5 dimensions | 76.48 |
| Tables | grits_trm_composite | 84.56 |
| Visual Grounding / Layout | rule_pass_rate | 81.83 |
| Content Faithfulness | content_faithfulness | 86.63 |
| Semantic Formatting | normalized_text_score | 66.32 |
| Charts | chart_data_point | 63.08 |
vllm serve \
--served-model-name kdl-frontier-parser-nano \
--max-model-len 8192 \
--gpu-memory-utilization 0.85 \
--max-num-seqs 24 \
--trust-remote-code \
--limit-mm-per-prompt '{"image":1}'
This model is not a single-shot end-to-end parser. It runs as a pipeline: detect layout, crop each region, then call the model again per region with a task-specific prompt.
Each task uses a fixed prompt (note the leading newline):
| Task | Prompt |
|---|---|
| Layout | \nLayout Detection: |
| Text | \nText Recognition: |
| Table | \nTable Recognition: |
| Formula | \nFormula Recognition: |
| Figure | \nImage Analysis: |
Table recognition returns OTSL. Other output formats are left to the caller.
--trust-remote-code and --limit-mm-per-prompt '{"image":1}' (one image per request).enable_thinking=False in the chat template.skip_special_tokens=False when decoding.temperature=0).Feed page images, not PDFs. Chat UIs (e.g. open-webui) with free-form prompts will not work — use the prompts above.
The ParseBench score is an end-to-end pipeline measurement — this model served via vLLM plus deterministic rule-based post-processing of model output — consistent with how all ParseBench providers are evaluated (every provider is a submitter-hosted endpoint). No other learned models, classifiers, or ensembles are involved: single model, single pass.
Built by KoreaDeep, a document-AI company. The larger KDL-Frontier-Parser-ultra is available through DEEP Agent.
From the published model card. Full card on the HuggingFace links in the sidebar.
Using it via the API
Once AxForge deploys kdl-frontier-parser-nano for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (kdl-frontier-parser-nano below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/chat/completions \
-H "Authorization: Bearer $AXFORGE_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"kdl-frontier-parser-nano","messages":[{"role":"user","content":"Hello"}]}'
Create an account — your API key is available in the console. 3M free tokens every 30 days with every new account.