Home / Guides / DeepSeek V4.1 Flash

Published September 26, 2026 · routes and prices checked September 26, 2026 · applies to pgup-ai/jbot-review-action v0

DeepSeek V4.1 Flash, released 2026-09-10, is free for code review through Cline’s free tier and costs $0.14 per million input tokens on OpenRouter. It’s a thorough reviewer and a slow one. On OpenCode Go, small pull requests took 7 to 13 minutes in our tests and a 234 KB change took up to 29. Through Command Code, a 16 KB change took about six minutes.

Free Cline setup in three steps

1. Save your Cline login. Run cline auth, then save the whole ~/.cline/data/settings/providers.json file as the repository secret CLINE_AUTH_JSON. The Cline guide covers the details.
2. Commit the workflow. Add the file below as .github/workflows/jbot-review.yml. The cline-free/ segment selects Cline’s free tier.
3. Open a pull request. J-Bot reads the base…head diff and posts diff-anchored findings with a verdict. A second session checks blocking findings before they post.

name: J-Bot Code Review
on:
  pull_request: { types: [opened, reopened, ready_for_review, synchronize] }

concurrency:
  group: jbot-review-${{ github.event.pull_request.number }}
  cancel-in-progress: true

permissions:
  contents: read
  pull-requests: write
  issues: write
  checks: read

jobs:
  review:
    if: github.event.pull_request.draft == false
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v7
        with: { fetch-depth: 0 }
      - uses: pgup-ai/jbot-review-action@v0
        with:
          model: cline/cline-free/deepseek-v4.1-flash
          cline-auth: ${{ secrets.CLINE_AUTH_JSON }}
          github-token: ${{ secrets.GITHUB_TOKEN }}

Cline caps each free model per day and doesn’t publish the size. On another free model, we hit the cap after 363 requests. For steady daily use, a metered route is cheap:

      - uses: pgup-ai/jbot-review-action@v0
        with:
          model: opencode-go/deepseek-v4.1-flash
          opencode-api-key: ${{ secrets.OPENCODE_API_KEY }}
          github-token: ${{ secrets.GITHUB_TOKEN }}

Nine routes, nine exact model ids

The first segment of each id selects the provider. Prices are per million input and output tokens from each live catalog on 2026-09-26.

Command Code accepts low, high and max effort for this model, with no medium, and J-Bot maps its effort setting onto those tiers.

How it performed

Review time grows with the pull request. These are OpenCode Go runs from September 23 to 26, two to four per pull request. Some used J-Bot’s defaults and some used variants we were testing, so read the ranges as rough.

• Handing it context barely helps. J-Bot’s context pack cut Space Bunny’s turns by 45% and DeepSeek’s by 8%.
• Command Code was quicker. Through Command Code, the same model reviewed a 4-file, 16 KB change to J-Bot’s own repository in 339 to 380 seconds, with 12 to 22 tool calls per session.
• It went to the web. A production review of a two-file frontend change took 12 minutes. Nine of them went mostly to web searches, page fetches and short scripts that pulled a grid library’s source from a CDN. The model wanted to know how the library groups rows. J-Bot now strips the web and code-execution tools from OpenCode review sessions and blocks curl and wget in their shell. A claim about a library’s internals has to come from Context7 or from the library’s code in the repository. Without either, the reviewer has to phrase it as an open question at advisory severity.
• Reading less cost a finding. We tried telling the guideline pass to read only the guidance J-Bot hands it. It made 41% fewer tool calls across two pull requests. On one of them it also missed a written testing rule in both runs, and the unchanged pass caught it both times. The rule was in its prompt the whole time. We kept the pass free to read.
• On Cline’s free tier it ran out of time verifying. With Cline reading the checkout, a 12-file review took 706 seconds. Most of its tool calls were shell commands, and verification hit its 300-second budget, so its three findings were held back.
• Low effort still reasons a lot. OpenCode passes the effort setting through and DeepSeek honors it, but at low effort it still produced about 44,000 reasoning tokens on a 25 KB diff.

If you need a review in minutes, run the model through Command Code or pick a faster free model such as Space Bunny. On OpenCode Go, give big changes room. The 234 KB change took up to 29 minutes, and J-Bot’s default budget is 30 minutes. A review that runs out of time fails instead of posting partial coverage, so raise time-budget-minutes for changes that size.

If your code reaches a library through your own wrappers, set enable-context7: true and pass context7-api-key. On auto, J-Bot turns Context7 on only when the diff touches dependencies, API clients or an ORM. On Cline’s free tier, expect a few tool-using reviews a day before the cap.

Where the diff goes

• The free route runs under Cline’s terms. Cline’s documentation says free-model usage may be used to improve model performance and quality. Keep private code on a metered route whose data policy you’ve read.
• Open weights, hosted routes. The weights are public, so you can serve the model yourself and connect J-Bot through the OpenAI-compatible provider.
• On Cline, every tool is approved. Cline works in the checkout in plan mode with its shell and write tools auto-approved, and a checkout’s .cline/hooks and .clinerules load. Its tools include web search, so the model can send search queries of its own. J-Bot documents this as an accepted risk on CI runners, so use the Cline route on repositories where you trust the people opening pull requests.
• The diff goes only where you point it. The review runs on your GitHub Actions runner, and J-Bot sends the diff only to the provider you configure.
• Fork pull requests can’t read the key. GitHub doesn’t pass repository secrets to pull_request workflows from forks.

FAQ

Related

Step 5 Preview, free on OpenCode Zen for a limited time, found the same number of known issues as DeepSeek V4.1 Flash on two production pull requests. It was slower on one and faster on the other. Read the Step 5 Preview vs DeepSeek V4.1 Flash comparison.

We later tested whether extra search context and slimmer compliance could improve this baseline. Read the DeepSeek V4.1 Flash optimization results.