Wald 4B
Data: JevBench v1.6.40, published 2026-10-22
Capability 59.8 · rank #60 of 139 on the open-weights board
Last measured: 2026-10-09 · measurement release: v1.6.2
Licence not stated
intelligence
41.1
calibration
78.4
speed
82.2
cost
54.3
Composite (secondary)
40.0 · Composite rank #53
Cost and measurement conditions
$0.033 per 1,000 decisions (estimated)
Self-hosted open weights, no bookable tariff. v1.5-M2 base-model reference rule: base model Qwen/Qwen3.5-4B (model card base_model) -> DeepInfra Qwen/Qwen3.5-4B, USD 0.03/M input and USD 0.15/M output, frozen 25 Sep 2026 price cut-off snapshot (METHOD-v1.5-ADDENDUM-PRICING-INTERPRETATION-1 I-2/I-3; listing deprecated after the cut-off, stays the frozen v1.5 reference). Output tokens priced at the reference output price. Read 2026-10-08.
Measured p50 latency: 0.031 s (on-GPU, no network, loopback; not directly comparable with API latency, which we time end to end from our measuring host, network included)
Ranking and cap use: 0.21 s (est. incl. network (2x + 150 ms))
Self-hosted model: measured p50 0.031 s on-GPU, no network (timed on our GPU over loopback). Not directly comparable with API latency, which we time end to end from our measuring host, network included. The ranking and latency cap use the same estimate for every self-hosted row: 2 × measured + 150 ms = 0.21 s. Model authors can ask us to time a hosted endpoint instead (on request).
x2 + 0.15 s (assumption, not measured)
Setup not stated