Qianfan-OCR BASE
Qianfan-OCR BASE · Q4_K_M · by Reza2kn
hf.co/Reza2kn/Qianfan-OCR-GGUF:Q4_K_M
Reza2kn · Q4_K_M · on ollama · quantizer build
Measured by one node on hardware we do not own, and signed by each of them. What machines here actually proved — never what the card claims.
matrix built 6 Nov 2026 · every field verified against the signature of the node that produced it, and re-verifiable by you: each signed figure carries the exact bytes the node signed (signing_payload_b64) and the signature over them, and the ed25519 public key is embedded in node_did. effective_ctx is the context length a node PROVED by recall, never the length a model card advertisescontext declared32Kwhat the runtime reported. A node attests it was told this; nobody attests it is true.
context proved by recall32Kthe largest size at which a machine could still find tokens planted across the whole prompt — start, middle and end, all of which had to come back.
A machine here made it use everything the runtime declared.
Languages, proved
Each question was put entirely in its own language and script, and the answer had to be right. A model with no coverage cannot parse the question, so answering in English is a failure here, not a pass. 6 proved of 10 asked — a language absent from the probe set was never asked, and is not a claim either way.
Capabilities, measured
Speech outprobed, and failed
The model itself turned text into audio — identified from the container bytes, not from what the engine labelled them, so an error page announced as audio cannot pass. Distinct from this gram running a separate text-to-speech engine: an operator choosing between them is choosing between two architectures.Reasons about codepassed
Asked to predict exactly what a short program prints. This is the half of coding that matters for agent work and that writing valid syntax does not demonstrate: following state through control flow.Writes codepassed
Asked for a specific function and checked with the Go compiler’s own parser. Nothing is executed — running model-written code to score a model would be a security hole opened for a metric — but syntactic validity is a fact rather than an opinion.Embeddingsprobed, and failed
The engine was asked for an embedding of a short text and returned a real, non-zero vector.Follows instructionspassed
Given a plain constraint on its output format and checked for exact obedience. This separates an instruct-tuned model from a base one — a base model answers fluently and ignores every instruction, which then looks like a dozen unrelated weaknesses instead of one.Sustained outputpassed
Asked to produce a long structured answer and checked for length. A model that stops after a couple of hundred tokens cannot write a report, however capable it is otherwise.Structured outputpassed
The ENGINE was asked to constrain decoding to a schema, and the answer conformed. This is stronger than politely asking for JSON and hoping: the grammar makes invalid output unreachable, which is what an operator actually builds on.Extended thinkingpassed
The model emitted reasoning on the engine’s dedicated reasoning channel before answering. Read from that channel rather than by scanning the answer for tags, which is why models that reason are no longer reported as models that do not.Synthesises sourcespassed
Given three documents with one fact split across them, and required to combine rather than quote. No single document contains the answer, so a model that retrieves without reasoning cannot pass.Tool callingprobed, and failed
The node asked the model to call a function and checked that it called the RIGHT one with a well-formed argument — not merely that it emitted a tool name.Counts in imagespassed
Shown a row of shapes and asked how many. Reading rendered text and grasping a scene are different abilities, and a model can do the first with no spatial understanding at all — which is what charts, shelf photographs and document layout actually need.Multiple images at oncepassed
Given two images and asked to compare them. Many engines and models accept one image per turn and silently drop the rest, which turns a comparison into a confident answer about half the evidence.Visionpassed
A four-digit code was rendered into an image and the model had to read it back. A model that cannot see cannot guess four digits, and a model that can has no reason to fail — so this passes and fails for the right reason, which describing a picture never did.Spatial reasoningpassed
Asked which of two shapes is larger and on which side — both ways round, so a coin flip cannot pass. Reading glyphs, counting objects and understanding layout are three different abilities, and only the third answers "what is next to what", which is what charts, diagrams and shelf photographs turn on.Tool loop finishedprobed, and failed
Whether the conversation ENDED after the tool call, or the model kept calling until the turn budget ran out. Passing “tool calling” and failing this means the model will call a tool in production and never come back. A model chosen on the first flag alone is the reason an agent silently stops delivering work.Audioprobed, and failed
Given audio and asked to transcribe it.Faithful to tool resultsprobed, and failed
The model was handed a list through a tool and had to report every item back. Calling a tool and understanding its answer are different abilities: a model can produce a perfect call, receive nine items, and confidently report three.signed by this networkEvery line traces to a node signature.
What machines here proved
context proved by recall32K
peak throughput ever signed17.56 tok/s · did:epn:002408…dae679
resident while loaded21.2 GiB (15.4 on card) · did:epn:002408…dae679
machines that measured it1
samples behind those numbers1
regions it was proved in1
from the public record · unsignedollama /api/show; the node attests that the runtime reported these, not that they are true. Attested by did:epn:002408…dae679.The only unsigned block on this page. We attest we read these from the runtime — not that they are true. Nobody signs a model card.
What the runtime says about it
context declared32K
parameters4.42B
parameter count4,42,03,43,296
quantisationQ4_K_M
familyqwen3
formatgguf
Proven across regions
Measured by
ranked on the provider standings
The machine that measured it
nothing is averaged — the machine is what you are choosingdid:epn:002408…dae679Singapore · 190464 · 0.40.15 · on host · 6 Nov 2026x86_64 · nvidia · 48.8 GiB pooled
32Kctx provedrecalled at every size asked
17.56tok/s now46 samples · 224s21.2 GiB resident · 15.4 GiB on card · 3.1 GiB on disk
✗ Speech out✓ Reasons about code✓ Writes code✗ Embeddings✓ Follows instructions✓ Sustained output✓ Structured output✓ Extended thinking✓ Synthesises sources✗ Tool calling✓ Counts in images✓ Multiple images at once✓ Vision✓ Spatial reasoning✗ Tool loop finished✗ Audio✗ Faithful to tool results✓ 6 languages
How far back it remembers, machine by machine
Filled: the needle came back at that prompt size · outlined: asked and lost · blank: not asked · trained for 32K. 0 walks ended because the model forgot, 0 because the machine could not hold the prompt.
| machine · build | 4K | 8K | 16K | 32K | why it stopped |
|---|---|---|---|---|---|
| Amit KhetanNVIDIA L4 · Q4_K_M by Reza2kn | 32K recalled at every size asked |
Carbon per million tokens
Lowest build on each machine · 1 of 1 read off a power sensor, the rest modelled from the parts · fewer grams is better
- Amit Khetan671 g5.11 J/tok · sensor
Carbon is location-based: signed energy × the yearly average of the grid where the machine signed its place (world grid average (Singapore not in the table); Ember Global Electricity Review 2025 (2024 generation), location-based). Facility overhead is not included. A machine on its own solar is not credited until it can prove it.
Run this where your data already is
Tell us the workload, whose machines it should run on, and which jurisdiction it answers to.