OpenAI compatible API · Attested · Public status

Meta: Llama 3.3 70B Instruct vs Qwen3.8 Max

Meta: Llama 3.3 70B Instruct vs Qwen3.8 Max: 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

Meta: Llama 3.3 70B Instruct has the lower cheapest prompt+completion route on TrustedRouter. Meta: Llama 3.3 70B Instruct has more provider fallback routes, while Qwen3.8 Max has the larger context window. Probe-backed speed data is shown when enough recent samples exist.

$0.564425/1MMeta: Llama 3.3 70B Instruct cheapest route

$6.964055/1MQwen3.8 Max cheapest route

1096 msMeta: Llama 3.3 70B Instruct fastest measured p50 TTFT via tinfoil

not enough dataQwen3.8 Max fastest measured p50 TTFT

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.

Meta: Llama 3.3 70B InstructQwen3.8 Max

Model idmeta-llama/llama-3.3-70b-instructqwen/qwen3.8-max

Publisher Cerebras Novita AI

AI IQ — IQ 121#26

Context131,072 tokens1,000,000 tokens

Credits provider routes114

Cheapest route$0.564425/1M$6.964055/1M

Cached input$0.1055/1M to $0.633/1M$0.21733/1M to $0.26375/1M

Privacy posturehas provider E2EE routeprovider posture varies

Fastest measured p50 TTFT1096 ms via tinfoilnot enough data

Highest measured throughputnot enough datanot enough data

Recent route uptime range100.00%100.00%

Modes chat chat

Meta: Llama 3.3 70B Instruct routes

Overview11 Credits routes
PricingInput, cached input, and output rates
BenchmarksTrustedRouter and external sources
ProvidersAll serving providers

Qwen3.8 Max routes

Overview4 Credits routes
PricingInput, cached input, and output rates
ProvidersAll serving providers

Related comparisons

Browse every comparison

Meta: Llama 3.3 70B Instruct vs Z.ai: GLM 5.242 combined provider routes
Qwen3.8 Max vs Z.ai: GLM 5.235 combined provider routes
Meta: Llama 3.3 70B Instruct vs MoonshotAI: Kimi K334 combined provider routes
DeepSeek: DeepSeek V4 Flash 0731 vs Meta: Llama 3.3 70B Instruct33 combined provider routes
Meta: Llama 3.3 70B Instruct vs Z.ai: GLM 5.333 combined provider routes
Meta: Llama 3.3 70B Instruct vs Z.ai: GLM 5.3 Flash31 combined provider routes
Meta: Llama 3.3 70B Instruct vs MoonshotAI: Kimi K2.630 combined provider routes
Meta: Llama 3.3 70B Instruct vs OpenAI: gpt-oss-120b30 combined provider routes

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="meta-llama/llama-3.3-70b-instruct",
    messages=messages,
)

Questions

Which should I use, Meta: Llama 3.3 70B Instruct or Qwen3.8 Max?

Is Meta: Llama 3.3 70B Instruct or Qwen3.8 Max cheaper?

The current cheapest TrustedRouter route is $0.564425/1M for Meta: Llama 3.3 70B Instruct and $6.964055/1M for Qwen3.8 Max. The comparison uses current catalog prices and updates as provider pricing changes.

Is Meta: Llama 3.3 70B Instruct or Qwen3.8 Max faster?

Current measured p50 time to first token is 1096 ms for Meta: Llama 3.3 70B Instruct and not enough data for Qwen3.8 Max. These are routed probe measurements, not vendor-advertised speeds, and update as new samples arrive.

Can I test Meta: Llama 3.3 70B Instruct and Qwen3.8 Max with the same API?

Yes. Use the same OpenAI-compatible TrustedRouter base URL and API key, then change only the model id between meta-llama/llama-3.3-70b-instruct and qwen/qwen3.8-max. This makes side-by-side evals possible without maintaining two provider integrations.