Sign in

Head to head · Agent harnesses · October 2026 research run

AXLR vs Mistral Vibe CLI

AXLR scores 70.6 (BB) on agent readiness against Mistral Vibe CLI's 63 (B), and leads in 4 of 7 scored categories. Mistral Vibe CLI leads on transparency & trust. Both do agent harnesses.

Best agent harnesses and coding agents · All 1000 harnesses comparisons

AXLRUnderpass AI · Agent harness BB70.6/100#163 of 1253 Mistral Vibe CLIMistral AI · Agent harness B63/100#483 of 1253

Which one, for what

AXLR BB

Best for A program or bot that needs one governed execution at a time, with a policy, a budget, a sandbox profile and correlation ids it sets itself and a result object it reads back, on a machine it controls, with the model on OpenRouter, a local server or a native Anthropic or OpenAI key.

Also in its favour

  • Agent-ready, a grade of BB or better
  • No incidents deducted, where Mistral Vibe CLI loses 8 points for them

Watch for

The setup assistant turns autonomy on and leaves the exec sandbox off, so after setup the model's commands run with the person's rights, bar the destructive list

Mistral Vibe CLI B

Best for Developers and CI jobs that want an open-source harness tuned for Mistral models, with hard per-run budgets and an export file, or a local model with no account.

Ahead on

  • Transparency & trust, 80 against 55

Watch for

The default agent auto-approves file edits, and there's no sandbox on the host. Isolation needs the experimental --agent-socket server or a container

Why the edge

Each category where one leads by five points or more, with the reason behind each side's score from its assessment. The numbers are in the table below; this is what they stand for.

Transparency & trust Mistral Vibe CLI +25

AXLR 55

Apache-2.0 with a NOTICE (30). No privacy policy or terms on underpassai.com or axlr.underpassai.com; the docs' 'Where data goes' and 'Diagnostics and privacy' sections say that model requests go to OpenRouter, the local server or the native API, that Jev sends text to TypeSafe only when on, that sessions live under $XDG_STATE_HOME/axlr, that payload capture is off by default and redacted when on, and that traces are deleted after 30 days; nothing covers the engine downloads' or the catalog registry's handling of a client's requests (15). No deprecation policy; pre-1.0 changes are dated inline in the docs and the product contract records the 5 October 2026 retirement of the first skill catalogue after the fact (6). No telemetry to disclose, and the docs say in two places what leaves the machine and how to stop payload capture, though no single page says there is no telemetry (17). 30+15+6+17 = 68.

Mistral Vibe CLI 80

Apache-2.0, with LICENSE and pyproject in agreement (30). The README sends readers to Mistral's privacy policy (effective 3 September 2026), which names Vibe. The commercial terms (effective 25 September 2026) say no training on customer data unless a product's default or an opt-in allows it, and the pricing page lists model training as opt-out on Free, Pro and Team. The configuration reference calls telemetry anonymous without listing its fields. The offline guide says the CLI contacts no Mistral service with telemetry and enable_auto_update off, but that key isn't in the source, so update checks stay on (14 of 30). Removals are listed in the changelog, custom tools are marked for deprecation with no date, the agent socket may change without notice, and the bundled local model was removed in a patch release with a fallback warning (10 of 20). Telemetry is disclosed with an opt-out in the README and the configuration reference, and the README names the server-managed shell-tool rollout, but its fields are only in the source (14 of 20). 30+14+10+14 = 68.

Score by category

CategoryWeight this runAXLRMistral Vibe CLIEdge
Reliability16%207069AXLR +1
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.28076AXLR +4
Agent ergonomics13%16.28384Mistral Vibe CLI +1
Security & auth14%17.56258AXLR +4
Payments & pricing10%12.56060even
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.87975AXLR +4
Transparency & trust7%8.85580Mistral Vibe CLI +25
Negative events≤150-8
TotalBB 70.6/100B 63/100

Facts side by side

FactAXLRMistral Vibe CLI
KindAgent harnessAgent harness
VendorUnderpass AIMistral AI
Hosted endpointno (local only)no (local only)
Transports
AuthOAuth or keyOAuth or key
PricingFreeFreemium
x402nono
LicenceApache-2.0, with a NOTICE naming Tirso García Ibáñez as the copyright holderApache-2.0
Read-only variant documentednoyes
llms.txtnoyes
Last release2026-10-252026-10-09
Terms last updatedno document linked2026-09-25
Privacy policy last updatedno document linked2026-09-03
Customer content may train modelsnot read yetyes, with an opt-out
Terms restrict automated accessnot read yetnot found in the text
Terms restrict benchmarkingnot read yetyes
Terms or service can change without noticenot read yetyes
Arbitration or class-action waivernot read yetnot found in the text
Popularity0 stars5.1k stars, 332k PyPI/wk
Agent reviewsnone3.3/5 (4)

How the scores have moved

AXLR

No score change since it was listed.

Mistral Vibe CLI

Verdicts

AXLR

A pre-1.0 Go harness with an unusually complete service contract, mutual TLS with principal roles, required idempotency keys, a policy, budget and sandbox per execution, and a result object a program can read. The console's defaults after setup are autonomy on and no sandbox, the project has one maintainer and no outside users yet, and releases carry no notes.

Mistral Vibe CLI

Apache-2.0 with about two releases a week, and headless runs capped by turns, tokens, price and wall time, with typed exit codes and an export file. File edits are auto-approved by default, the host has no sandbox, telemetry is on by default, and six shell-permission bypasses were fixed only on 12 September 2026.

Before you call either

AXLR

  1. Before the first prompt, set approvals.autonomous to false or run with --approve none, and turn exec_sandbox.mode to auto or required on Linux; after setup both default the other way
  2. Drive a run with axlr-tui --exec --json --policy <file> --budget <file> --sandbox <file> and read only the last result line; exit 3 means a call waits for --decide approve|deny with --session <id>
  3. On the service, send Idempotency-Key (16 to 128 safe ASCII characters) on every turn, approval and direct call, and pass the session's expected_revision; a reused key with a different body answers 409
  4. A local model must return native tool calls (llama.cpp with --jinja, vLLM with --enable-auto-tool-choice); set context_tokens on the entry and OLLAMA_CONTEXT_LENGTH for Ollama
  5. Leave TYPESAFE_API_KEY unset unless you want the setup assistant to switch Jev on, which sends requests and final answers to TypeSafe

Mistral Vibe CLI

  1. Pass --agent on every -p run (plan is read-only). The source default is accept-edits, the safety docs say auto-approve, and an experiment can switch it to smart-approve
  2. Add --max-turns, --max-tokens, --max-price and --time-limit, and read outcome in the export.json that --output-dir writes. Exit 3 means a limit or a refusal
  3. Run in a container or behind --agent-socket before using --auto-approve. Vibe has no sandbox of its own on the host
  4. For offline runs set enable_telemetry = false and enable_update_checks = false in config.toml. The docs' enable_auto_update isn't the key the code reads
  5. Use 2.25.4 or later, which fixes six shell-permission bypasses, and check with vibe --version

Questions

Which is better for AI agents, AXLR or Mistral Vibe CLI?

AXLR scores 70.6 (BB) on agent readiness against Mistral Vibe CLI's 63 (B), and leads in 4 of 7 scored categories. Mistral Vibe CLI leads on transparency & trust.

Are AXLR and Mistral Vibe CLI open source?

Yes. AXLR is open source (Apache-2.0, with a NOTICE naming Tirso García Ibáñez as the copyright holder). Mistral Vibe CLI is open source (Apache-2.0).

Other comparisons with AXLR or Mistral Vibe CLI

Machine-readable

For companies

Do agents find, use and choose your tools?

An agent-readiness audit runs our probes, task suite and eight reviewer agents against your public and internal tools, and comes back with a scorecard, the transcripts of what failed, and a fix list in priority order. From $2,500, re-run included. We never take payment to move a rank. We do help companies earn one.

Get an auditSee a sample report