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Kimi K3.1 Pro: test the service before buying the infrastructure · The Augur Dispatch

• 0:00
  SPEAKER_00: Kimi K3.1 Pro is already available to try.
• 0:03
  SPEAKER_00: Its downloadable weights are still promised for November 4th.
• 0:07
  SPEAKER_00: That difference changes the advice a business should hear today.
• 0:10
  SPEAKER_00: Start learning whether the hosted model helps, but keep the hardware purchase separate.
• 0:15
  SPEAKER_00: Artificial analysis has already published outside evaluations.
• 0:19
  SPEAKER_00: This isn't a release supported only by a vendor's own charts or enthusiastic social posts.
• 0:24
  SPEAKER_00: The evidence just doesn't answer every buying question.
• 0:28
  SPEAKER_00: This is the Augur dispatch for Monday, October 26, 2026.
• 0:34
  SPEAKER_00: Picture an engineering lead and a finance director looking at the same announcement.
• 0:38
  SPEAKER_00: The engineer wants to find out whether a difficult support workflow has become easier.
• 0:43
  SPEAKER_00: Finance wants to know whether the company is about to acquire an expensive new hobby.
• 0:48
  SPEAKER_00: Both have a point.
• 0:50
  SPEAKER_00: Auger's judgment is that the hosted model merits a bounded evaluation where data policy permits, while a self-hosting commitment needs evidence about the actual deployment.
• 1:00
  SPEAKER_00: Those decisions can happen on different schedules.
• 1:03
  SPEAKER_00: They probably should.
• 1:05
  SPEAKER_00: The case for testing is substantial enough to take seriously.
• 1:08
  SPEAKER_00: Artificial analysis reported K3.1 Pro in fourth place on its intelligence index at launch, with gains on tests of agents carrying out work.
• 1:17
  SPEAKER_00: Those results were published on October 23rd.
• 1:20
  SPEAKER_00: We shouldn't dismiss them because the downloadable files aren't here yet.
• 1:24
  SPEAKER_00: We also shouldn't turn a launch ranking into a forecast of how the model will perform in every office.
• 1:30
  SPEAKER_00: A benchmark supplies a defined set of problems and a way of grading them.
• 1:34
  SPEAKER_00: Your business supplies missing information, awkward exceptions, and a colleague who keeps the crucial detail in a separate spreadsheet.
• 1:42
  SPEAKER_00: Moonshot describes the model as 3 trillion class.
• 1:45
  SPEAKER_00: Artificial analysis lists about 2.8 trillion total parameters, the learned numerical values inside the model.
• 1:53
  SPEAKER_00: That rounded marketing category doesn't establish a jump in the underlying size.
• 1:57
  SPEAKER_00: Moonshot describes this as a version of K3 with more work on training after the initial model was built.
• 2:04
  SPEAKER_00: The distinction is useful, but the buying decision doesn't turn on counting parameters.
• 2:09
  SPEAKER_00: It turns on whether the service produces acceptable results at a cost the organization can justify.
• 2:15
  SPEAKER_00: For our hypothetical engineering lead, that means bringing actual resolved support cases to the evaluation, stripped of information that isn't approved for the service.
• 2:25
  SPEAKER_00: If the old system already handled the easy cases, another polished answer to an easy case tells the team little.
• 2:32
  SPEAKER_00: The harder decision starts when someone says the company should run the model itself.
• 2:37
  SPEAKER_00: Downloadable weights are the model's files.
• 2:40
  SPEAKER_00: They give a buyer the possibility of operating it outside the publisher's service, subject to the license and whatever equipment and software the model needs.
• 2:49
  SPEAKER_00: They don't supply the equipment.
• 2:51
  SPEAKER_00: For the earlier K3, Simon Willison reported a download of roughly 1.5 terabytes.
• 2:57
  SPEAKER_00: A multiverse computing article described about 3TB of graphics chip memory just to load it.
• 3:02
  SPEAKER_00: Those are different measurements, and neither is a verified deployment requirement for K3.1 Pro.
• 3:08
  SPEAKER_00: Amazon Web Services published a particular K3 setup using eight B300 graphics processors with fast connections between them.
• 3:17
  SPEAKER_00: That's more informative than simply adding every available graphics card to a spreadsheet and announcing that the company has enough memory.
• 3:24
  SPEAKER_00: A cluster has to move information between its chips, serve the workload at an acceptable speed, and leave room for the work happening during a request.
• 3:33
  SPEAKER_00: The arithmetic on spare equipment doesn't prove that arrangement will function.
• 3:37
  SPEAKER_00: Imagine the finance director asking whether the engineering team has a working deployment plan or a list of expensive parts.
• 3:45
  SPEAKER_00: That question can feel obstructive on announcement day.
• 3:48
  SPEAKER_00: It becomes rather helpful when a machine arrives and nobody can explain why it isn't doing the promised work.
• 3:54
  SPEAKER_00: For a team without that infrastructure, hosted access may remain the sensible option even after November 4th.
• 4:01
  SPEAKER_00: Control over the model is valuable only if the organization can afford to operate that control.
• 4:07
  SPEAKER_00: There's another reason to keep the purchasing process concrete.
• 4:11
  SPEAKER_00: On the Interconnects podcast, Florian Brand discussed allegations that promotion around the launch involved undisclosed payments.
• 4:18
  SPEAKER_00: Nathan Lambert referred to a screenshot and said he knew of no corroboration at that point.
• 4:24
  SPEAKER_00: That's an allegation worth examining.
• 4:26
  SPEAKER_00: It isn't proof that all the praise was purchased, and it doesn't invalidate the evaluation's artificial analysis has published.
• 4:33
  SPEAKER_00: Suspicion can become its own shortcut if we let it replace the work of checking different kinds of evidence.
• 4:40
  SPEAKER_00: The same care applies to a hosting company's promise that it serves a familiar model.
• 4:45
  SPEAKER_00: Moonshot introduced its Kimi vendor verifier alongside an earlier model, K2.6, after finding that serving choices could change behavior.
• 4:54
  SPEAKER_00: Its account discusses problems with settings and tool calls.
• 4:58
  SPEAKER_00: That gives buyers a useful question to ask.
• 5:00
  SPEAKER_00: It doesn't establish that the older verifier already certifies K3.1 Pro.
• 5:06
  SPEAKER_00: Ask what exact version was tested, under which settings, and what the host actually measured.
• 5:12
  SPEAKER_00: The strongest counterargument to waiting is that teams learn by using a model, and the hosted service already gives them that opportunity.
• 5:19
  SPEAKER_00: Auger agrees.
• 5:21
  SPEAKER_00: Waiting for infrastructure evidence should not become an excuse to ignore the evidence available now.
• 5:27
  SPEAKER_00: Our engineer can compare the hosted model against the current system this week.
• 5:31
  SPEAKER_00: Finance can decline to fund a permanent deployment until the comparison and the operating plan justify it.
• 5:37
  SPEAKER_00: Nobody needs to win the entire argument in one meeting.
• 5:41
  SPEAKER_00: The evaluation becomes useful when someone follows the work after the answer appears.
• 5:46
  SPEAKER_00: Consider a support draft that arrives sooner but takes longer to check because the explanation sounds convincing even when one detail is wrong.
• 5:55
  SPEAKER_00: The apparent time saving may have moved to the reviewer.
• 5:58
  SPEAKER_00: It may also be a real improvement.
• 6:00
  SPEAKER_00: You won't know if the measurement stops at generation.
• 6:03
  SPEAKER_00: TechCrunch reported a Nielsen survey, commissioned by Monday.com, in which nearly half of the managers surveyed said they were spending more time reviewing and guiding output.
• 6:14
  SPEAKER_00: That is self-reported experience, rather than a measured estimate of AI's net productivity effect.
• 6:20
  SPEAKER_00: It is still a reason to count review time.
• 6:22
  SPEAKER_00: For the proposed support test, let the engineering lead own the comparison and have the workflow owner judge acceptable resolutions.
• 6:30
  SPEAKER_00: Use the same cases and an agreed standard, including difficult cases where the existing system struggles.
• 6:36
  SPEAKER_00: Agree what improvement would count before looking at the new results.
• 6:40
  SPEAKER_00: Then review the evidence on November 4th.
• 6:43
  SPEAKER_00: Stop if the test would send sensitive information outside an approved boundary or exceed its agreed spending limit.
• 6:50
  SPEAKER_00: Expansion should depend on better accepted outcomes, without worse errors or a higher total handling cost.
• 6:56
  SPEAKER_00: The cost of this preparation is staff time that could have gone to current work.
• 7:01
  SPEAKER_00: Return to the finance director's desk with those results.
• 7:04
  SPEAKER_00: A shorter waiting time for customers is an outcome worth discussing.
• 7:08
  SPEAKER_00: A pile of generated drafts is another pile of work until somebody establishes what happened to it.
• 7:14
  SPEAKER_00: The lasting advantage, if the test succeeds, comes from the company's case history and the way it uses reliable answers.
• 7:22
  SPEAKER_00: Competitors can buy access to the same model.
• 7:24
  SPEAKER_00: They don't automatically acquire the knowledge of where your support process breaks.
• 7:30
  SPEAKER_00: There are still signals on the clock.
• 7:32
  SPEAKER_00: First comes the full weights release promised by November 4th, followed by usable deployment instructions and version-specific evidence from hosts.
• 7:41
  SPEAKER_00: The wider written dispatch also follows patching of vulnerable brotley decoders that handle untrusted compressed data, and whether finance teams count the effort of checking AI output.
• 7:52
  SPEAKER_00: It watches the timetable for OpenAI's companion hardware, which the cited coverage still describes as in development.
• 7:59
  SPEAKER_00: These are follow-up questions, separate from a dated prediction.
• 8:02
  SPEAKER_00: Today's auger call is that Moonshot will make the Kimi K 3.1 Pro weights publicly downloadable on or before November 4th, 2026.
• 8:12
  SPEAKER_00: The odds remain 55%.
• 8:14
  SPEAKER_00: A hit requires an official repository, model card, or blog post showing public wait files by that date in UTC.
• 8:22
  SPEAKER_00: Without that release by the deadline, it's a miss.
• 8:24
  SPEAKER_00: Hosted access doesn't satisfy the test.
• 8:28
  SPEAKER_00: Augur calls give predictions a deadline and explicit criteria.
• 8:32
  SPEAKER_00: You can follow them on the website.
• 8:34
  SPEAKER_00: The written brief with every source is at augerdispatch.ai.
• 8:39
  SPEAKER_00: The next useful purchase meeting should include the reviewer who checked the model's work.
• 8:44
  SPEAKER_00: That person can explain whether the new capability removed effort or merely delivered it to a different desk.
• 8:50
  SPEAKER_00: Portions of the Augur Dispatch are AI generated.
• 8:54
  SPEAKER_00: That is the Augur Dispatch for Monday, October twenty sixth, twenty twenty six.
• 8:59
  SPEAKER_00: Thank you for listening.