image2.5 from $0.0085 per 1K image · Seedance 2.5 from $0.0961/sec · cached LLM input from $0.40/M — one OpenAI-compatible endpoint at https://api.apimart.ai/v1, no monthly plan required. (observed 2026-09-17)

Get an API key · Live pricing · Model page

Why teams route through APIMart

  • One key, entire catalog. The same https://api.apimart.ai/v1 base URL and Authorization header reach the whole catalog behind one key and 300+ other image, video and language models — switch the model field, not your client.
  • $1 minimum, pay as you go. No subscription and no prepaid plan to size up front: top up from $1 and spend it on calls. There is no free quota to burn through first, so the price in this table is the price you pay.
  • The charge comes back in the response. Every call reports the amount billed (cost / credits_cost), so a spend number is read per call instead of guessed at month end.
  • Async by design. Submit, take the task_id, poll GET /v1/tasks/{id} — batching and retries are ordinary queue work, not a bespoke integration.

LLM gateway comparison without the marketing table: pick the dimensions that matter to you, weight them, and score the four gateway archetypes (self-hosted open source, managed control plane, relayed per-unit route, direct vendor API) with a script you can rerun when your requirements change.

Why archetypes instead of a vendor scorecard

Vendor feature matrices go stale in weeks, and a comparison written by an interested party is not a comparison. This repository keeps the part that stays true: the dimensions on which gateways differ, plus a scoring script so the weighting is yours. Named products appear only as examples of an archetype.

python tools/compare.py --show                                  # the criteria matrix
python tools/compare.py --weight control=3 --weight cost_transparency=3 \
                        --weight setup_effort=2 --weight ops_burden=1

The dimensions that actually differ

Dimension Question it answers Why it decides projects
Credential model How many keys does the caller manage? Key sprawl is the top operational cost of multi-vendor work
Response normalisation Is the envelope the same across providers? Parser drift after an API revision is a silent outage
Billing unit Which unit do you pay in? Per-image/per-second makes cost a multiplication; tokens require measurement
Retry safety Is there an idempotency mechanism? Without it, a timeout plus a retry bills twice
Timeout control Can you set request and job TTLs? Long generation jobs need a TTL you own
Observability What is exposed per request? Per-task cost, progress and status are the minimum for reconciling a bill
Self-hostable Can it run in your infrastructure? Decides data residency and egress review
Ops burden Who runs upgrades and incidents? The hidden line item in every "free" gateway

Run your own comparison in one afternoon

  1. Freeze a request set. 20–50 real prompts covering every surface you use (chat, streaming, tools, images, vision).
  2. Score the archetypes with tools/compare.py using weights your team agrees on — record who set which weight.
  3. Test two candidates for real. Same prompts, same acceptance rules; record p50/p95 latency, error classes, retry behaviour and cost per accepted artefact.
  4. Check the boring parts: key rotation, quota exhaustion behaviour, retention and region, and what happens to an in-flight job when you fail over.
  5. Only then decide, and keep the rollback as a configuration change rather than a code change.

What this repository is not

  • It is not a ranking of vendors, and it does not claim that any archetype wins: a two-person team and a platform team with an SRE rotation should reach different conclusions from the same matrix.
  • It is not a benchmark. Latency and price numbers belong in your own run, on your own prompts.

What that costs at scale

Workload Cost at the observed rates
1,000 GPT Image 2.5 renders (1K) $8.50
10 minutes of Seedance 2.5 at 480P (600s) $57.66
1M cached LLM input tokens from $0.40

Linear at the observed per-unit rate, no volume discount assumed. Snapshot 2026-09-17; re-check the live table before committing a budget.

First-call troubleshooting

Symptom Likely cause Fix
401 / invalid api key key missing, truncated, or a stray newline pasted into the header Re-copy it from the console; the header is Authorization: Bearer $APIMART_API_KEY
balance / credit error the account has no balance Top up from $1 in the console — there is no free quota to fall back on
429 concurrent requests on one key Back off, then retry the same request with the same Idempotency-Key
400 / model not found wrong route for the id: the per-unit alias needs its version, the official id must not send one Copy the exact model value from the route table above
task ends failed prompt rejected by the filter, or a reference image URL expired Re-submit with a new Idempotency-Key and re-host the reference image
result URL stops working result links expire Download the file as soon as the task reports completed
  • llm gateway comparison
  • ai api gateway
  • llm gateway open source
  • llm gateway vs proxy
  • ai api aggregator
  • openai compatible api
  • ai api pricing comparison

Start with $1. Get an API key → check live pricing → open the whole catalog behind one key in the model library. The first call is three steps: submit, poll task_id, read the charged amount off the response.

Purpose Attributed link Target
Browse the model catalog https://go.apimart.ai/k-dda2cc apimart.ai/model
Current pricing page https://go.apimart.ai/k-9f4ab7 apimart.ai/pricing
Get an API key https://go.apimart.ai/k-95b075 apimart.ai/keys

Outbound APIMart links are minted through the promo link API; hand-made tracking parameters are rejected by tools/check_links.py in CI.

Disclosure

This repository describes gateway archetypes and a scoring method. It is published to document that method, not to claim official status for any vendor; product names appear as examples and belong to their owners. Verify each cell against the vendor's documentation for your own account.

Repository map

README.md              comparison method, dimensions and workflow
data/gateways.json     archetypes, dimension values and scores (schema: llm-gateway-comparison-v1)
tools/compare.py       weighting and scoring
tools/check_links.py   attribution guard (CI)