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Request mechanics: billing, limits, latency, calibration and stability
TL;DR Community probes of the request itself (2026-09-16→23,
jev-1.13.0): billing is exactly input tokens × $0.042/M with output free, each request carries ~261 tokens of fixed overhead, the 32k/64k limits hold where the docs put them, latency stays flat to ~100 questions, and answers are stable but not bit-exact. Each figure is one person's run; official limits: Models, aliases, pricing, rate limits, context. Split from Measurements, access routes and open replicas on 2026-09-25.
Measured
| Number | Reported by | Setup | Caveat |
|---|---|---|---|
| 50 calls at 25 concurrent: 741 ms, no 429s; all 50 at once was slower (~1 s). Claim check on 16 labelled headlines: true 0.83-0.90, false 0.01-0.12 | Nate B. Jones | run through OpenRouter | One run; 25-way concurrency is a starting point, not a limit |
| ~30k tokens in ~160 ms; server time barely moved up to ~100 questions, then rose steadily; 1,500 questions still returned in a few hundred ms; a 200-option question was as quick as a 2-option one | Archer Hume, jev-1.13.0, 2026-09-17 |
192 + 148 sequential requests, shuffled, 8 repeats per size | Times are the x-envoy-upstream-service-time header: shared service, queueing included; not a hardware benchmark |
| Token accounting is additive: 268 input tokens for one minimal Noul, 276 for two, 318 for a Noul + 2-option Choice + 2-level Score; a 23k-token state with 5,000 questions was accepted | same | 311 accounting + 35 limit-boundary requests | verified against the 64k-per-request / 32k-per-branch budgets, state counted once (Models, aliases, pricing, rate limits, context) |
| Calibration: 10-bin ECE 0.031 over 1,200 MMLU items (990 in the 0.9–1.0 bin); MMLU-Pro 84.6%; fresh 3-digit multiplication 86.7% correct at mean top probability 0.83; two-step word problems 32% at 0.30; modular exponentiation 56% at 0.35 | same | 6,800 benchmark records + 190 generated maths items | Recomputed from recorded probabilities, not the API confidence field. Family averages hide bin-level error; maths is a documented weakness (Jev 1.13 jaggedness: known failure modes §2) |
| Option-set effects: reversing a ticket's options moved the top probability 0.84–0.89 → 0.93–0.96; one added irrelevant option moved the log-odds between two existing options +0.38 → +0.11 (mean −0.28, paired 95% ≈ −0.36…−0.19, lower in all 10 blocks) | same | 181 order + 96 reference-card + 50 block-randomised requests | unverified against docs — one scenario per template; advisory reading in Field reports: independent evaluations, critiques, open replicas |
output_tokens is billing arithmetic, not decoding: a Noul request costs 4 shared tokens + 15 per answer + the token length of each question id (which the docs say the model never sees); a 255-option response reported 2,714 |
same | 311 requests | Output tokens are free (Models, aliases, pricing, rate limits, context); never divide them by duration and call it speed |
Jev's tokenizer matches none of 192 public tokenizers across 415 probes (closest Qwen at 348/415); every digit is a separate token; 8 as count as 1 token, 16 as 4 |
same | 445 requests | unverified. Local tiktoken or character estimates drift both ways — leave headroom under the caps |
Billing is input tokens × $0.042/M, exactly: across 2,976 responses usage.cost matched to $0.000000000; 122,844 output tokens not charged. Fixed overhead ~261 input tokens per request (one-word state). Batching N = 2 / 4 / 8 questions saved a median 43–49% / 65–74% / 76–86% of input tokens (tiny → ~3,000-token state); 8 questions in one call returned 7.7–8.6× faster than 8 serial calls; batched and single answers differed no more than identical repeats (Noul 0.005, Score 0.010, Choice top never changed) |
blowxian, jev-fanout-bench | via OpenRouter (provider TypeSafe, jev-1.13-20260917), 2026-09-23, $0.156; every request, response and checksum published |
Price and free output verified (Models, aliases, pricing, rate limits, context). 261 fits the docs' one-sentence Noul example (296 input_tokens) and Archer Hume's 268: a calculator counting only state + questions undercounts small requests. Serial timing; synthetic English tickets. Pattern: Speculative fan-out |
| Per-request formula (R² ≥ 0.999): |
same, round 2 | 479 billed requests + 8 over-limit probes; answers withheld, citing the MCA's competing-models term | Limits verified: the brackets contain 32,768 and 65,536 (State: what you send Jev); "overhead counts toward neither" unverified. No question cap is documented (Archer Hume sent 5,000). His estimator at jevpricing.com claims 1.4% median error over 365 requests (unverified) |
| Translating the ticket moved yes/no answers 3–5× the English repeat noise; translating the questions too moved them further and cost 9–48% more tokens. Reordering Choice options never changed the top option; removing descriptions or paraphrasing moved probabilities 2–10 points. Over 960 reworded or translated answers, the lowest-confidence third of Choice answers moved 15× more than the top third (Spearman ρ −0.79) and held all five top-option changes (Score 7.5×, ρ −0.51) | same | same run | English-first verified (Models, aliases, pricing, rate limits, context): keep questions in English. Order: Archer Hume (above) saw reversal move the top probability 0.84–0.89 → 0.93–0.96 and position change a reference option's hit rate. Stable winner, moving numbers: not a contradiction, but both unverified and the docs are silent. Re-check thresholds after any rewording |
| Latency flat to 100 questions: 3 / 25 / 100 / 400 questions → 521 / 1,242 / 4,017 / 15,417 input tokens and 712 / 690 / 714 / 1,336 ms (cold connection, Netherlands, 2026-09-17); warm 250–580 ms over 16 calls | Colin de Vries, jevclient | README table, one location | (15,417 − 521) ÷ 397 ≈ 37.5 tokens per added question (our arithmetic), fitting the formula above and Archer Hume's flat-to-~100 curve |
Server time p50 75–90 ms (x-envoy-upstream-service-time); warm round trip ~290 ms p50 from a machine 185 ms (TCP) away, ~1.2 s on a new connection. 16 requests at a time was fine; all 100 at once pushed round-trip p50 to ~2 s (server time still ~90 ms) and drew 529 Overloaded retries |
teyhouse, jev-secret-detection (no licence) | 100-case set, jev-1.13.0 |
verified in direction: docs say "about 100 ms" (How to build software with System One); 529 is retryable (HTTP status codes, rate limits, retry semantics), so cap client concurrency. His "AWS us-west-2" is unverified. Accuracy: Failure reports: where Jev broke, lost, or was the wrong tool |
| 19,772 requests in ~252 s at concurrency 16, 32.06M input tokens, ~$1.35 at list price | bitnovus, jev-spam-eval | full paired run, no API errors | ~4,700 requests/min, ~127k tok/s (our arithmetic): above the documented 1,200 rpm, under 250k tok/s. jev-sec-bench's 662 in 22.7 s is ~1,750/min. Limits "can change without notice" (Models, aliases, pricing, rate limits, context); don't plan on headroom |
| Jev billed more input tokens than GPT-5.6 Terra for the same prompt: 360 vs 153 (8-way), 952 vs 828 (77-way), so per decision it was 40–49× cheaper than Terra, below the price-list ratio. Median 0.33 s; slowest of 791 calls 1.42 s | Adel Dahani, AY Automate | via OpenRouter, 3,955 calls, $1.53 total; agency blog | Compare billed cost per decision, not price per token. Accuracy: Head-to-head: Jev against other models and methods |
How to measure and what not to assume
- Don't assume bit-exact repeats. Archer Hume's probes found small differences between identical requests, between duplicate questions in one request, and in key order. Measure on distributions, not equality; don't key a cache or golden test on exact probabilities.
- Measure latency as Archer Hume did for comparable numbers: server-reported upstream time (
x-envoy-upstream-service-time), requests one at a time in shuffled order, several repeats per size. Local wall-clock adds your network and client. - Batch before you parallelise. One request per question pays the ~261-token overhead each time and waits serially; ask everything about one
statein one call (Speculative fan-out, Cookbook: Parallel questions), then cap concurrency (16 was fine, 100 at once drew529s).
Related
- Measurements, access routes and open replicas — workload cost and speed, replicas, access routes; Field reports: independent evaluations, critiques, open replicas — what these numbers mean when advising
- Models, aliases, pricing, rate limits, context, HTTP status codes, rate limits, retry semantics, Confidence vs probability — the official contract
Sources
Links are inline in each row. Raw captures (raw/x-repos/, raw/nate/, raw/community/) are in the private repo; Nate B. Jones's material is used with his permission and credited.