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agentic coding
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heads up: the downloaded files contain your token in cleartext, and moving them to the shown paths will overwrite any existing .claude, .codex, or opencode configs. back up what's there first if you already use these CLIs.
agentic support is on limited testing and might have bugs, feedback is welcome
paths for
01install, leave it closed (install docs)
02download & move to these paths
create .claude if it doesn't exist. dot-folders may be hidden in finder. create the folder: mkdir $HOME\.claude in powershell — explorer won't make dotfolders.
03open terminal, run claude
01install, leave it closed (install docs)
02download & move to these paths
create .codex if it doesn't exist. dot-folders may be hidden in finder. create the folder: mkdir $HOME\.codex in powershell — explorer won't make dotfolders.
03open terminal, run codex
01install, leave it closed (install docs)
02paste the token above, then export these
export GOOGLE_GEMINI_BASE_URL=https://vip.jewproxy.tech/proxy/google-ai export GEMINI_API_KEY=YOUR_PROXY_TOKEN
token travels in cleartext, just like the downloaded files. sandbox mode does not propagate GOOGLE_GEMINI_BASE_URL into the sandbox — run unsandboxed against this proxy (upstream google-gemini/gemini-cli#2168).
03open terminal, run gemini
01install, leave it closed (install docs)
02download & move to this path
create ~/.config/opencode if it doesn't exist. the config uses this proxy as an OpenAI-compatible upstream. create the folder: mkdir $HOME\.config\opencode in powershell. if you run OpenCode in WSL, use the WSL path instead.
03open terminal, run opencode
the generated config includes Gemini and OpenRouter when available. edit model or the provider model list to use any model this proxy exposes.
how to use step by step

jewproxy = api access to many ai models, billed via one token. every app needs the same three values: a base url, an api key, and a model name.

01→ the universal recipe
  1. copy a base url from this page
  2. set your api key to your jewproxy token
  3. set the model (depends on the endpoint and tags shown)
02→ sillytavern, full walkthrough
  1. open the api panel (the plug icon at the top)
  2. choose chat completion
  3. choose source custom (openai-compatible)
  4. paste the base url
  5. paste your jewproxy token as the api key
  6. type the model name, or use the model selector
  7. click connect, then send a 1-line test message
for gemini 4 carbon or gemini 4 argon, use the google-ai endpoint. same setup, different base url.

for DeepSeek V4.1 Flash, use https://vip.jewproxy.tech/proxy/deepseek/v1 with your proxy token and model deepseek-flash, which serves the DeepSeek-V4.1-Flash-1017 snapshot. this is the native DeepSeek endpoint, not a third-party model catalog.

model limits are 1M context (1,000,000 tokens) and 384K output (393,216 tokens, including thinking). this proxy's operator caps still apply. upstream output defaults are 8,192 without thinking, 65,536 with thinking, and 131,072 at max effort.

use reasoning_effort none, low, high, or max; thinking defaults to high. keep assistant reasoning_content in tool histories. JSON object output is supported; schema-enforced structured output is not advertised.

Flash accepts image input on this proxy. prefix caching is automatic and best-effort. tools and streaming use the same chat endpoint.

deepseek-v4-pro keeps serving DeepSeek-V4-Pro-0813 at Pro prices, text input only.

official guides: prices and UTC peak/off-peak schedule · thinking and tools · image input

03→ same 3 values in other apps
lobe chat, librechat, big-agi, openai libraries for python and js, plus your own discord and telegram bots. all use the same base url + api key + model pattern.
04→ support
access, billing, payment, or anything else: buy.jewproxy.tech

a visual ui for both image and video generation. no api setup required.

01→ the url
https://img.jewproxy.tech
02→ the steps
  1. open the frontend
  2. pick image or video at the top
  3. pick a model or preset
  4. write a clear prompt
  5. adjust options (size, count, duration for video, etc.)
  6. press generate
  7. save, tag, compare, or export the result
this frontend is hosted separately from the proxy. its model picker may lag behind the api catalog. use the image api tab for direct requests; the local admin image page is a history ledger, not a generator.

run export TOKEN="..." with your jewproxy token. every command below sends $TOKEN, never a provider key. choose native openai for its Images API, openrouter for the normalized image route, or google for native generateContent. selecting a model updates the curl command.

01→ pick the model
this tab uses the native openai Images API with bare model ids. the selector contains only this proxy's discovered inventory. the GPT Image 2.5 aliases are gpt-image-2.5-flare and gpt-image-2.5-sunburst; their pinned snapshots are gpt-image-2.5-flare-2026-09-08 and gpt-image-2.5-sunburst-2026-09-08. GPT Image 2.6 adds gpt-image-2.6-flare and gpt-image-2.6-sunburst, with no dated snapshots. they appear in the selector only when discovered. for OpenRouter, choose its tab and the corresponding openai/-prefixed alias.
live list
GET https://vip.jewproxy.tech/proxy/openai-image/v1/models. check current availability and model-specific capabilities.
02→ send the request
post model and prompt to /v1/images/generations. omitting the model still selects gpt-image-2. native requests use n (1–10), size, and quality. GPT Image accepts auto, low, medium, and high; only 2.5 and 2.6 add xhigh and max. for 2.5 and 2.6, a custom WIDTHxHEIGHT must use multiples of 16, edges up to 3840, aspect ratio at most 3:1, and 655,360–8,294,400 pixels. sizes above 2560x1440 are experimental. 2.5 and 2.6 also support background: "transparent", which requires output_format: "png" or "webp". edits use /v1/images/edits with up to 16 reference images. 2.6 also accepts complexity (low, medium, or high; omitted means high, with no extra fee). 2.6 generations can return an animated GIF with output_format: "gif", frame_count (2–64, default 9), and frame_duration_ms (20–2000, default 200); size is then per frame, auto or multiples of 16, and frames may be smaller than the still-image minimum. GIF quota holds cover every frame and n; auto frames split an assumed 8,294,400-pixel request budget, so a default 9-frame GIF at auto quality holds 60,588 output tokens. that budget and GIF billing are unpublished, so holds are estimates that settle on provider usage and can be below the final charge. edits do not offer GIF. SVG output and markup edits are rejected.
curl --request POST \
  --url https://vip.jewproxy.tech/proxy/openai-image/v1/images/generations \
  --header "Authorization: Bearer $TOKEN" \
  --header "Content-Type: application/json" \
  --data '{"model": "gpt-image-2", "prompt": "a lighthouse at dawn, oil painting"}'
03→ read the result
this route is synchronous. HTTP 200 includes the finished image at a proxy-hosted data[0].url. GPT Image returns inline b64_json bytes upstream; the proxy mirrors them to that URL. response_format is a proxy-owned option, not an upstream GPT Image parameter. there is no job id or polling. native gpt-image quotas count raw tokens unless a shared OpenAI quota is configured; that shared quota converts input and output costs separately at the GPT-5 baseline ($1.25/$10 per million).
lands at
data[0].url (proxy-hosted)
04→ when it fails
  1. 403 Model family 'gpt-image' is not enabled on this proxy. an admin must allow-list the family.
  2. 402 OpenAI image generation is unavailable or not yet verified on this proxy. report the upstream-key issue to the admin.
  3. 429 You've exceeded your token quota for this model type. means quota. other 429s may be rate or concurrency limits; wait before retrying.
read error.message first, then error.code and error.type when present.
do not send a GPT Image model as the top-level model to /chat/completions or /responses. these examples use the Images API.
GPT Image 2.5 and 2.6 Flare and Sunburst have the same token-based prices, not a flat per-image fee. per million tokens: $5 text input ($1.25 cached), $8 image input ($2 cached), and $30 image output. output tokens depend on dimensions and quality; at low and medium, 2.6 estimates about 4.2× and 3.3× the 2.5 output tokens. provider usage settles the charge; an actual USD cost, including $0, takes precedence over an estimate. missing usage and auto settings need conservative estimates. usage.cost or usage.total_cost_usd records actual cost; usage.estimated_cost_usd marks an estimate. see 2.5 Flare and Sunburst, 2.6 Flare and Sunburst, and OpenAI pricing.

for local cli agents (claude code, codex, or opencode).

  1. open the agentic coding button on this page (the one to the right of how to use)
  2. pick claude code, codex, or opencode
  3. download the generated config file(s)
  4. place each file at the path the popup shows for your os (mac / linux / windows)
  5. open the cli. it should pick up the config
the config files store your token in clear text. don't commit them to a repo or share screenshots.
not needed for
sillytavern or any chat frontend
questions
buy.jewproxy.tech
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