I recently read a paper, which showed a mathematical model for performance scaling of research groups in different scientific branches. I'm aware you were originally asking for smaller "cognitive tasks" and project-like group-processes in the comments, but output and quality of publications/patents is probably anyway a better and more objective measure on a larger scale. Also, the paper shows that optimal group sizes in different academic disciplines varies strongly, so comparing, e.g. single groups in math and biology solving tasks is probably not very meaningful (Jeromys 1st comment) for your original question and only valid for exactly that discipline/distinct cognitive task, which would make a general analysis/conclusions tricky/impossible.
Assumptions:
The extent to which a group’s research quality is higher or lower than
average is a function of many parameters such as the innate calibre, education
and experience of its members, the quality of managerial support and of facilities
and infrastructure, the impact of external and international collaborations, the
prestige and confidence inspired by the institution and by past successes, etc. All
of these parameters contribute to the quality of an individual group but, in
general, research quality is size independent according to this argument. [...] However, it would be naive to retain this viewpoint alone because it
neglects the importance of interactions between group members.
The model:
A group has $N$ members, therefore the total number of pairs of individuals along which channels of communication can open is
$N_{T}=N(N-1)/2$ (quadratical scaling)
So group quality tends to rise continuosly with quantity. The main statement of the article however is that the rise of quality is independent of group quantity after a group reaches a upper critical mass ($NN_{C}/2$ linear scaling) and increaes only with much smaller slope further, basically because a single researcher can only communicate meaningfully with a limited number of other researchers (sub-groups build within big groups, specialization)
Comparison with available data:
I will not copy paste all the data fits here, look them up in the paper, well worth and interesting, many academic disciplines are compared in different countries and match the model and quadratic scaling quite well in different academic disciplines.
So the scaling for groups is the same, as mainly determined by meaningful face-to-face communication, the different critical mass among different academic disciplines has probably to do with the necessary amount of researcher you need to run, for example, a high-technology research laboratory (many students who master the single instruments) vs. mathematics (formalized language, not the broad spectrum of problems like in natural sciences) vs. humanities (reading and discussing a lot of literature)
Implications:
To improve overall research performance in a country, increase groups below the size of the critical mass instead of further increasing of already abnormal big research groups, where a slope for performance scaling dependent on $N$ still exists, but is much smaller than below the critical mass
Side note: Apart from this critical research group size I'm aware of a new trend in bigger companies to forbid or restrict e-mailing for the majority of employees, because only a marginal amount of this e-mails is really important according to studies (15% I rememember mentioned by Volkswagen AG, but not the source currently)
References
Kenna R, Berche B (2011). Critical masses for academic research groups and consequences for higher education research policy and management. Higher Education Management and Policy 23 (3), 9-29.