OpenAI compatible API · Attested · Public status

Ling-3.0-flash vs Meta: Llama 3.3 70B Instruct

Ling-3.0-flash vs Meta: Llama 3.3 70B Instruct: compare current API pricing, context, provider routes, privacy, p50 latency, and OpenAI-compatible access.

Verify gateway
Onebase URL to migrate
100sof models and routes
0prompt or output logs. Always.
Compare routesProviders, price, context, and policy posture in one view.
Use auto when uptime mattersKeep a primary model and let fallback handle provider failures.
Same API shapeUse the OpenAI client and set the model you want.

Practical read

Monthly evidence

Ling-3.0-flash has the lower cheapest prompt+completion route on TrustedRouter. Meta: Llama 3.3 70B Instruct has more provider fallback routes, while Ling-3.0-flash has the larger context window. Probe-backed speed data is shown when enough recent samples exist.

$0.2532/1MLing-3.0-flash cheapest route
$0.564425/1MMeta: Llama 3.3 70B Instruct cheapest route
not enough dataLing-3.0-flash fastest measured p50 TTFT
959 msMeta: Llama 3.3 70B Instruct fastest measured p50 TTFT via sambanova

Prices and live route measurements can change. Use the monthly reports when you need a stable evidence window, then run a small task-specific eval before choosing a production default.

Ling-3.0-flashMeta: Llama 3.3 70B Instruct
Model idinclusionai/ling-3.0-flashmeta-llama/llama-3.3-70b-instruct
AI IQ IQ 92#103
Context262,144 tokens131,072 tokens
Provider routes418
Cheapest route$0.2532/1M$0.564425/1M
Privacy postureprovider posture varieshas provider E2EE route
Fastest measured p50 TTFTnot enough data959 ms via sambanova
Highest measured throughputnot enough datanot enough data
Recent route uptime range100.00%100.00%
Modes chat chat

Ling-3.0-flash routes

Meta: Llama 3.3 70B Instruct routes

Related comparisons

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Production choice

Pick a default model. Keep fallback enabled.

TrustedRouter is useful when you know the model you want, but still need provider rollover, budget limits, usage records, and a prompt path you can verify.

OpenAI clientPython
client = OpenAI(
    base_url="https://api.trustedrouter.com/v1",
    api_key="sk-tr-v1-..."
)

response = client.chat.completions.create(
    model="inclusionai/ling-3.0-flash",
    messages=messages,
)

Questions

Which should I use, Ling-3.0-flash or Meta: Llama 3.3 70B Instruct?

Ling-3.0-flash has the lower cheapest prompt+completion route on TrustedRouter. Meta: Llama 3.3 70B Instruct has more provider fallback routes, while Ling-3.0-flash has the larger context window. Probe-backed speed data is shown when enough recent samples exist.

Is Ling-3.0-flash or Meta: Llama 3.3 70B Instruct cheaper?

The current cheapest TrustedRouter route is $0.2532/1M for Ling-3.0-flash and $0.564425/1M for Meta: Llama 3.3 70B Instruct. The comparison uses current catalog prices and updates as provider pricing changes.

Is Ling-3.0-flash or Meta: Llama 3.3 70B Instruct faster?

Current measured p50 time to first token is not enough data for Ling-3.0-flash and 959 ms for Meta: Llama 3.3 70B Instruct. These are routed probe measurements, not vendor-advertised speeds, and update as new samples arrive.

Can I test Ling-3.0-flash and Meta: Llama 3.3 70B Instruct with the same API?

Yes. Use the same OpenAI-compatible TrustedRouter base URL and API key, then change only the model id between inclusionai/ling-3.0-flash and meta-llama/llama-3.3-70b-instruct. This makes side-by-side evals possible without maintaining two provider integrations.

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