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.
Practical read
Monthly evidenceDeepSeek 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.
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/llama-3.3-70b-instruct
DeepSeek: DeepSeek V4 Flash Vision Exp routes
Meta: Llama 3.3 70B Instruct routes
- Overview10 Credits routes
- PricingInput, cached input, and output rates
- BenchmarksTrustedRouter and external sources
- ProvidersAll serving providers
Related comparisons
Browse every comparison- Meta: Llama 3.3 70B Instruct vs Z.ai: GLM 5.343 combined provider routes
- Meta: Llama 3.3 70B Instruct vs Z.ai: GLM 5.242 combined provider routes
- Meta: Llama 3.3 70B Instruct vs Z.ai: GLM 5.3 Flash42 combined provider routes
- Meta: Llama 3.3 70B Instruct vs MoonshotAI: Kimi K338 combined provider routes
- DeepSeek: DeepSeek V4 Flash 0731 vs Meta: Llama 3.3 70B Instruct36 combined provider routes
- DeepSeek: DeepSeek V4 Flash Vision Exp vs Z.ai: GLM 5.336 combined provider routes
- DeepSeek: DeepSeek V4 Flash Vision Exp vs Z.ai: GLM 5.235 combined provider routes
- DeepSeek: DeepSeek V4 Flash Vision Exp vs Z.ai: GLM 5.3 Flash35 combined provider routes
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.
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.