These scores were compiled from the linked sources. These published scores were not independently tested here. Different prompts, precision, thinking budgets and tools can change results.
JEVBench · public 231
89.61 / 100
Micro accuracy across 48 Easy, 72 Original and 111 Hard-public decisions using the typed-decision serving bundle. Not an official leaderboard rank.
Benchmark efficiency: 1.276 published score points per GB of selected weights. This ratio is not an inference-speed measure; check the test settings to see whether the score covers the selected quantization.
Test settings: 207/231 public decisions correct, publisher self-run; JEVBench harness 1bcc55eb6c8cffde2306b3db03ede39b61c6152a; typesafe adapter, one request at a time, released serving bundle.
Typed-decision specialist. Requires pinned patched SGLang bundle; validated on one H200 143GB. Bytes cover all 16 shards, not peak RAM. Not an official JEVBench rank or general chat score.
Context and version evidence: The repository and file name identify the selected model. Revision hashes are shown above when recorded. Tested context length, full hardware configuration and run date are not consistently recorded in this snapshot. Only settings explicitly stated in each benchmark record are known.
The 70.214 GB figure covers model weights in this file. It excludes the context cache, runtime, operating system and any separate multimodal files. It is not a measured RAM requirement or a token-generation speed.
These complete configurations pass the initial weight-size check for the selected 70.21 GB file. Allow extra memory for context and software. Check the model’s runtime notes and your inference software before buying.
Listing evidence: 2026-09-24. Amazon.com price shown in an owner-supplied screenshot reviewed 24 Sep 2026; capture time not provided. Excludes shipping, import charges, tax and optional discounts. This is a dated reference, not a live checkout quote.
Memory matches are estimates, not tested compatibility or speed. As an Amazon Associate I earn from qualifying purchases.
Confirm model architecture and quantization support in your runner. The selected weights use 70.214 GB; this excludes context cache, runtime buffers and other programs.
These are the first listed tiers that pass our reserve policy, not measured minimum requirements. System RAM and VRAM remain separate. Use the memory tool to change the reserve for your context and runner.