Project AURIONAI Use-Cases Research & Innovation

Frontier Pretraining Scaling

Training a new base model at or near the top-5 compute of its release date (Epoch's frontier definition).

Tier Grades

feasible

Tier A: Frontier AI labs

feasible

high confidence

Observed actors are frontier labs, with 12 developers holding a 1e25 FLOP model by June 2025 at tens of millions of dollars per run.

not feasible

Tier B: Indonesian AI labs

not feasible

high confidence

The cheapest anchor is DeepSeek-V3 at $5.576M for the final run alone, and the notes verify no Indonesian national compute programme, BRIN facility or ITB GPU inventory (T11 Part E item 2).

not feasible

Tier C: Institution units such as ITB

not feasible

high confidence

Academic teams typically have 1 to 8 GPUs for days, against 2.788M H800 GPU hours for the cheapest frontier final run.

not feasible

Tier D: Organisations such as SEMAI (PoT, PoC, PoV)

not feasible

medium confidence

The notes give no anchor placing proof-of-concept firms anywhere near 1e25 FLOP runs; their compute scale is not described.

Where this comes from
Tiers: a) frontier AI labs, b) Indonesian AI labs, c) institution units such as ITB, d) organisations such as SEMAI delivering proof of technology, concept and value. Each rationale cites the anchors below.

Anchors

  • Compute1e25 to 1e26 FLOP; a 1e25 run costs tens of millions of dollars; first 1e26 FLOP model Grok-3 (Feb 2025); frontier compute grows 4 to 5x per year; final-run cost grows about 2.4x per year, projected above $1B by 2027; DeepSeek-V3 final run 2.788M H800 GPU hours, $5.576M, excluding ablations.
  • DataDeepSeek-V3 14.8T tokens; GLM-4.5 23T tokens.
  • Team size (proxy)Proxy only (author count of an exemplar paper, not a headcount): not sourced in the notes. R&D staff are 29 to 49% of development cost for selected frontier models.
  • Time horizonMonths per run; 4 to 5x per year compute growth.
  • Shelf-life signalsOpen models lag closed by about 14 months weighted, Final-run figures understate total cost because ablations and staff are excluded
  • Pipeline roleTier A produces frontier base models and, when released as open weights, the substrate that Tier B, Tier C and Tier D adapt; the roughly 14-month open lag sets how stale that substrate is.
Where this comes from
Team size is a proxy (author counts of exemplar papers), not a headcount.

Who and What

Exemplars
SpaceXAI (xAI)Grok-3DeepSeek-V3Z.ai (Zhipu)GLM-4.5
Observed actors
Linked models
+109
Google DeepMindGemini 3.6 FlashLLMproduced byMetaMuse Spark 1.1LLMproduced byOpenAIGPT-5.6 LunaLLMproduced byOpenAIGPT-5.6 SolLLMproduced byOpenAIGPT-5.6 TerraLLMproduced byAnthropicClaude Fable 5LLMproduced byCohereCommand A+ (command-a-plus-05-2026)multimodal LLMproduced byGoogle DeepMindGemini 3.5 Flashmultimodal LLMproduced byBaiduERNIE 5.1LLMproduced byMistral AIMistral Medium 3.5 (v26.04)multimodal LLMproduced byOpenAIGPT-5.5LLMproduced byMetaMuse SparkLLMproduced byAlibaba (Qwen)Qwen3.6 Max PreviewLLMproduced byAlibaba (Qwen)Qwen 3.6 PlusLLMproduced byGoogle DeepMindGemini 3.1 Pro (preview)multimodal LLMproduced byAnthropicClaude Opus 4.6LLMproduced bySpaceXAI (xAI)Grok 4.1 FastLLMproduced byOpenAIGPT-5.1LLMproduced byMistral AIMistral Medium 3.1 (mistral-medium-2508)multimodal LLMproduced byOpenAIGPT-5LLMproduced byAnthropicClaude Opus 4.1LLMproduced bySpaceXAI (xAI)Grok 4multimodal LLMproduced byByteDanceSeed1.6multimodal LLMproduced byAnthropicClaude Opus 4LLMproduced byMistral AIMistral Medium 3 (mistral-medium-2505)multimodal LLMproduced byOpenAIGPT-4.1LLMproduced byOpenAIGPT-4.1 miniLLMproduced byOpenAIGPT-4.1 nanoLLMproduced byOpenAIGPT-4o (March 2025, chatgpt-4o-latest)multimodal LLMproduced byOpenAIGPT-4o (March 2025 update)multimodal LLMproduced byBaiduERNIE 4.5multimodal LLMproduced byAlibaba (Qwen)Qwen2.5-MaxLLMproduced byGoogle DeepMindGemini 3 Promultimodal LLMproduced bySpaceXAI (xAI)Grok 2 (Dec 2024, grok-2-1212)LLMproduced byAnthropicClaude 3.5 Sonnet (Oct '24)multimodal LLMproduced byOpenAIGPT-4o miniLLMproduced byAnthropicClaude 3 Haikumultimodal LLMproduced byAnthropicClaude 3 Opusmultimodal LLMproduced byAnthropicClaude 3 Sonnetmultimodal LLMproduced byMistral AIMistral Large (Feb '24)LLMproduced byMistral AIMistral Medium (Dec '23)LLMproduced byPythia-1BLLMused by01.AIyi-lightningLLMproduced byAlibaba (Qwen)Qwen3.5 Max PreviewLLMproduced byAlibaba (Qwen)Qwen3.7 MaxLLMproduced byAlibaba (Qwen)Qwen3.7 Max PreviewLLMproduced byAlibaba (Qwen)qwen3.7-plusLLMproduced byAlibaba (Qwen)qwen3.8-flashLLMproduced byAlibaba (Qwen)Qwen3.8-Max-PrimeLLMproduced byAlibaba (Qwen)qwen3.8-omni-flashmultimodal LLMproduced byAlibaba (Qwen)qwen3.8-omni-flash-realtimemultimodal LLMproduced byAmazonNovaLLMproduced byAmazonNova 2.0 OmniLLMproduced byAmazonNova 2.0 Pro PreviewLLMproduced byAmazonNova ActLLMproduced byAmazonNova LiteLLMproduced byAmazonNova MicroLLMproduced byAmazonNova PremierLLMproduced byAmazonNova ProLLMproduced byAnthropicClaudeLLMproduced byAnthropicClaude 3.5 HaikuLLMproduced byAnthropicClaude 3.7 SonnetLLMproduced byAnthropicClaude Haiku 4.5LLMproduced byAnthropicClaude Mythos 5LLMproduced byAnthropicClaude Mythos 5.1LLMproduced byAnthropicClaude Opus 4.5LLMproduced byAnthropicClaude Opus 4.7LLMproduced byAnthropicClaude Opus 4.8LLMproduced byAnthropicClaude Opus 5LLMproduced byAnthropicClaude 4 SonnetLLMproduced byAnthropicClaude Sonnet 4.5LLMproduced byAnthropicClaude Sonnet 4.6LLMproduced byAnthropicClaude Sonnet 5LLMproduced byAppleApple server PT-MoE model (Private Cloud Compute)LLMproduced byBaiduERNIELLMproduced byBaiduERNIE 4.0LLMproduced byBaiduERNIE 5.0LLMproduced byByteDanceDola-Seed 2.0 ProLLMproduced byByteDanceSeed2.1LLMproduced byGoogle DeepMindGeminimultimodal LLMproduced byGoogle DeepMindGemini 2.0multimodal LLMproduced byGoogle DeepMindgemini-2.5-computer-use-preview-10-2025LLMproduced byGoogle DeepMindGemini 2.5 Flashmultimodal LLMproduced byGoogle DeepMindGemini 2.5 Flash-LiteLLMproduced byGoogle DeepMindGemini 2.5 ProLLMproduced byGoogle DeepMindGemini 3.1 Flash-LiteLLMproduced byGoogle DeepMindGemini 3.5 ProLLMproduced byGoogleGemini 3 Flashmultimodal LLMproduced byGooglePaLM 2LLMproduced byHuawei (Huawei Cloud)Pangu 5.5 NLPLLMproduced byiFlytekiFlytek SparkLLMproduced byMetaMuse Spark 1.2LLMproduced byMetaMuse Spark (family)LLMproduced byOpenAIGPT-3.5 Turbo (0613)LLMproduced byOpenAIGPT-4LLMproduced byOpenAIGPT-5.2LLMproduced byOpenAIGPT-5.4LLMproduced byOpenAIGPT-5.6 CyberLLMproduced byOpenAIGPT-5 miniLLMproduced byOpenAIGPT-6LLMproduced byGoogle DeepMindGemini 3.5 Flash-Litemultimodal LLMproduced byGoogle DeepMindGemini 3.8 Flash CyberLLMproduced byOpenAIGPT (GPT-1)LLMproduced bySpaceXAI (xAI)GrokLLMproduced bySpaceXAI (xAI)Grok 4.20LLMproduced bySpaceXAI (xAI)Grok 4.5LLMproduced bySpark 4.0-2024-10-14LLMproduced byStepFunStep 5 PreviewLLMproduced byThinking MachinesInklingLLMproduced by

Papers

Where this comes from
The papers to read first: where the direction began, its current best, and a survey when one exists.

Sources

  1. Training compute of frontier AI models grows by 4-5x per year epoch.ai https://epoch.ai/blog/training-compute-of-frontier-ai-models-grows-by-4-5x-per-year
  2. How much does it cost to train frontier AI models? epoch.ai https://epoch.ai/blog/how-much-does-it-cost-to-train-frontier-ai-models
  3. Over 30 AI models have been trained at the scale of GPT-4 epoch.ai https://epoch.ai/data-insights/models-over-1e25-flop
  4. How many AI models will exceed compute thresholds? epoch.ai https://epoch.ai/tools/model-counts
  5. Data on AI models epoch.ai https://epoch.ai/data/notable-ai-models
  6. DeepSeek-V3 Technical Report arxiv.org https://arxiv.org/html/2412.19437v1
  7. GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models arxiv.org https://arxiv.org/abs/2508.06471
  8. Open vs. closed AI: How behind are open models? epoch.ai https://epoch.ai/blog/open-models-report

To cite this page: Project AURION, AI Use-Cases Research & Innovation, "Frontier Pretraining Scaling", https://aurion.semai.id/topics/frontier-pretraining-scaling/, records of October 2026.