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Yes, the network performance will increase with memory. There are no specifics as there is no definitive performance since Lambda compute is abstracted from you and it is also protocol and application specific. You should benchmark your function with various memory sized to determine where you meet your requirements.
If your lambda is interacting with resources inside your VPC or with AWS services, you should VPC enable your lambda function if you haven't done so already - https://docs.aws.amazon.com/lambda/latest/dg/configuration-vpc.html
Also make use of interface VPC endpoints for AWS services. That way the traffic goes over the AWS network and not the internet - https://docs.aws.amazon.com/vpc/latest/privatelink/create-interface-endpoint.html
That's not an answer to anything I wrote, I was asking about network resources being affected by memory configuration like vCPU, nothing relating to VPC configuration.
All Lambda functions get the same type of network interface with the same bandwidth. However, the more memory you give your function, the more CPU it gets, which allows it to actually drive the network bandwidth, up to the limit that the network interface supports. This is why you will see an increase in bandwidth only until some point.
What's surprising to me is that at 1GB memory I'm seeing 1mb/s, at 2GB I see 2mb/s, but after that it makes no meaningful difference switching it to 10GB. This seems really low, and there's no indication on what ranges AWS lambda operates in so I can't tell if this is within expected levels or not. Same code on my own machine hitting the same target gets 7mb/s down.