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DeepSeek: DeepSeek V4 Flash Vision Exp vs Meta: Llama 3.3 70B Instruct

Try both on us. Starter credit covers your first requests, then one key routes DeepSeek V4 Flash Vision Exp and Llama 3.3 70B Instruct. Switch by changing the model name.

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

DeepSeek V4 Flash Vision Exp has the larger context window. Meta: Llama 3.3 70B Instruct has the lower published input-plus-output rate and more Credits provider routes. There is not enough recent probe data to compare speed.

$1.8568/1MDeepSeek: DeepSeek V4 Flash Vision Exp cheapest route
$0.564425/1MMeta: Llama 3.3 70B Instruct cheapest route
not enough dataDeepSeek: DeepSeek V4 Flash Vision Exp fastest measured p50 TTFT
1234 msMeta: Llama 3.3 70B Instruct fastest measured p50 TTFT via scaleway

The price comparison adds each route's rate for one million input tokens and one million output tokens; your cost depends on your input/output mix. 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.

DeepSeek: DeepSeek V4 Flash Vision ExpMeta: Llama 3.3 70B Instruct
Model iddeepseek/deepseek-v4-flash-vision-expmeta-llama/llama-3.3-70b-instruct
AI IQ IQ 121#40 —
Context1,048,576 tokens131,072 tokens
Credits provider routes310
Cheapest route$1.8568/1M$0.564425/1M
Cached input$0.01477/1M to $0.02954/1M$0.1055/1M to $0.633/1M
Privacy postureprovider posture varieshas Confidential route (E2EE + ZDR)
Fastest measured p50 TTFTnot enough data1234 ms via scaleway
Highest measured throughputnot enough datanot enough data
Recent route uptime rangenot enough data100.00%
Modes chat chat decide

DeepSeek: DeepSeek V4 Flash Vision Exp routes

Meta: Llama 3.3 70B Instruct routes

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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="deepseek/deepseek-v4-flash-vision-exp",
    messages=messages,
)

Questions

Which should I use, DeepSeek: DeepSeek V4 Flash Vision Exp or Meta: Llama 3.3 70B Instruct?

DeepSeek V4 Flash Vision Exp has the larger context window. Meta: Llama 3.3 70B Instruct has the lower published input-plus-output rate and more Credits provider routes. There is not enough recent probe data to compare speed.

Is DeepSeek: DeepSeek V4 Flash Vision Exp or Meta: Llama 3.3 70B Instruct cheaper?

The current cheapest TrustedRouter route is $1.8568/1M for DeepSeek: DeepSeek V4 Flash Vision Exp and $0.564425/1M for Meta: Llama 3.3 70B Instruct. The comparison uses current catalog prices and updates as provider pricing changes.

Is DeepSeek: DeepSeek V4 Flash Vision Exp or Meta: Llama 3.3 70B Instruct faster?

Current measured p50 time to first token is not enough data for DeepSeek: DeepSeek V4 Flash Vision Exp and 1234 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 DeepSeek: DeepSeek V4 Flash Vision Exp 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 deepseek/deepseek-v4-flash-vision-exp and meta-llama/llama-3.3-70b-instruct. This makes side-by-side evals possible without maintaining two provider integrations.

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