I admit I am piggybaking off of @Alex but hopefully adding some clarity with the charts and data provided in the answer.
First, we need to get some data:
I combined this in a Julia DataFrame to obtain:
Plotting GDP from all 3 sources shows the following:
The IMF data is also more forward looking (includes forecasts, which were excluded here). The World Bank metadata offers some interesting insight:
... different countries use different definitions, methods, and
standards. World Bank staff review the quality of national accounts
data and sometimes make adjustments to improve consistency with
international guidelines. Nevertheless, significant discrepancies
remain between international standards and actual practice. Many
statistical offices, especially those in developing countries, face
severe limitations in the resources, time, training, and budgets
required to produce reliable and comprehensive series of national
You can find some more details in this answer. For example, the UK "quickly" added £10 billion to GDP by accounting for illegal drugs and prostitution. This is still nothing compared to Nigeria, which literally doubled its GDP over night.
Nonetheless, as already suggested, it is mainly the difference in FX rates that causes the results to be so different in this case:
We can convert the UN Figure to the shadow FX rate via this line
df[!, "UN Inofficial GDP"] = df[!,"UN GDP"]./df[!,"inofficial"].*df[!,"official"]
Plotting UN and WB GDP data looks like this now (IMF is practically identical to UN so I omitted it):
With regards to which series is more accurate - WB would be a more sensible choice. The official rate is kept artificially high. The effect is similar to Real vs Nominal GDP. The actual value that matters is the productive capacity. With high inflation, prices rise, and even if real productivity declines, as long as prices rise more, nominal GDP increases. That is what you observe in the GDP values using the official exchange rates as well. It makes it look as if GDP almost doubled since 2017, when in fact productivity declined.
Last but not least, it is difficult to get accurate numbers in circumstances like these. There may even be a large amount of unreported informal economic activity with barter or goods being consumed within the household (e.g. agriculture). This would in turn underestimate GDP, but to be honest, I have no experience with developing countries national accounting, and as such, this is a purely speculative addition.