China vs US token volume and value, and what 1.5M Ascend 950s running DeepInfer could output
The piece compares China and US token totals, output volume and revenue per token, notes DeepSeek's $0.60 vs Opus's $25 output price, and estimates 1.5M Ascend 950s on DeepInfer could produce ~190T output tokens per day.
China produces more AI tokens. The US produces more AI value per token. Ascend stack significant in 2027. [ Research using Claude ] Two numbers get mixed up in token debates. Total tokens count everything a model processes, mostly input: prompts, documents and long agent contexts it reads. Output tokens are the text it actually generates, a small fraction of the total and the part that costs the most compute. Total tokens. China reported ~500T/day in June [1], mostly ByteDance's Doubao consumer chat [2]. The US has no national figure. Google (~107T/day) [3] plus OpenAI's API (~22T/day) [4] are the biggest disclosed pieces, and the full US total is probably in the same range as China's.¹ Output tokens. China's chat-heavy mix plausibly yields ~25–50T of output per day out of that 500T. US traffic is dominated by agentic coding, which reads huge contexts and writes relatively little, so US output is likely ~6–25T/day.² On both measures, China is plausibly ahead. Value per token. Here the US is far ahead. DeepSeek charges ~$0.60 per million output tokens; Claude Opus charges $25 [5][6]. Anthropic alone runs at ~$47B/yr [7]. The US spends far more compute and earns ~10× the revenue per token.³ What's coming. DeepSeek just open-sourced DeepInfer, the engine serving its V4.1-Flash model [8]. One ~2,400-GPU cluster handles 155T total tokens/day [9], and the engine officially supports Huawei's Ascend 950. Huawei could have ~1.5M Ascend 950s deployed by spring 2027 [10][11]. If they all ran V4.1-Flash on DeepInfer, they could generate roughly 190T output tokens/day, 4–8× China's output today. That estimate is conservative, based on DeepSeek's coding-heavy traffic; chat-heavy use could roughly double it. It's possible because V4.1-Flash uses only 16B active parameters per output token, so each chip generates tokens cheaply [12].⁴ Notes ¹ US total tokens. Google reported 3.2 quadrillion tokens/month in May 2026; 3.2Q ÷ 30 ≈ 107T/day. OpenAI reported 15B tokens/min on its API in March; 15B × 1,440 ≈ 21.6T/day, or roughly 25–60T/day with ChatGPT included. Anthropic, Meta, xAI and most of Microsoft don't disclose. The disclosed sum is ~150–250T/day. Applying Google's ~7×/yr growth since those dates gives a plausible current US total of ~300–500T/day, comparable to China's June figure. Both are self-reported, and they likely count tokens differently. ² Output share. Neither country publishes its input/output split, so these are assumptions. DeepSeek's production traffic is ~97% cache-hit input, ~2% uncached input and ~1% output [13]. Epoch models general chat at 8k in / 1k out (~11% output) and agentic use at 25k–128k in / 1k out (~1–4%) [14]. China at 5–10% output: 500T × 0.05–0.10 ≈ 25–50T output/day. US at 2–5%: ~300–500T × 0.02–0.05 ≈ 6–25T output/day. ³ Value per token. $25 ÷ $0.60 ≈ 40× on list output prices (Opus vs DeepSeek V4.1-Flash off-peak). Chinese state media itself puts domestic API prices at 1/3 to 1/20 of international competitors [15]. "~10× the revenue" is a rough judgment, not a measured ratio. Anthropic alone ($47B run-rate) plus OpenAI ($25B+) is far larger than any disclosed Chinese token revenue. ⁴ Ascend capacity calculation. Nvidia baseline (DeepSeek production, self-reported): 155T total tokens/day on ~2,400 SM100 GPUs. Per decode GPU, ~14k output tokens/s [13]. Scaling to Ascend: The 950DT has 4 TB/s memory bandwidth vs ~8 TB/s for B200 [16], and ~1 PFLOPS FP8 vs ~4.5 dense [17]. Decode at DeepSeek's ~230 tok/s per user is mostly bandwidth-bound. Assume 0.4× SM100 after a software haircut, so ~5.6k output tokens/s per 950DT. Fleet by ~April 2027: ~1.1M 950PR (prefill) + ~400k 950DT (decode), extrapolated from Epoch's 2026 estimate of ~750k 950PR and ~320k 950DT [10] plus the 2027 run rate. HBM supply caps the DT count [11]. Output: 400k × 5.6k tokens/s × 86,400 s ≈ 194T output tokens/day. Range: low ~90T (250k DT at 0.3×); high ~420T (700k DT at 0.5×). Against China today: 190T ÷ 25–50T ≈ 4–8×. Traffic mix: The 5.6k figure reflects DeepSeek's coding-heavy traffic (long contexts, ~1% output). Chat-heavy traffic raises decode throughput per chip and frees most 950PRs from prefill; they could decode at ~2–3k tok/s each. That gives a plausible ~350–450T output/day. Total tokens: In the coding-heavy case, total ≈ output × 100 ≈ 20 quadrillion/day. In the chat-heavy case, total ≈ output × 10 ≈ 3–5 quadrillion/day. Assumptions: The whole fleet runs this model at DeepSeek's utilization. No Ascend benchmarks have been published; these are spec-scaled estimates. References [1] TechNode, "China's daily AI token usage tops 500 trillion" (Aug 2026): https://technode.com/2026/08/28/chinas-daily-ai-token-usage-tops-500-trillion-as-compute-demand-grows/ [2] Pebblous, "China's 140 Trillion Daily Tokens as an Economic Metric": https://blog.pebblous.ai/report/china-token-economy-metric-2026-07/en/ [3] Shacknews, Google I/O 2026, 3.2 quadrillion tokens/month: https://www.shacknews.com/article/149205/google-3-2-quadrillion-monthly-ai-tokens [4] Panto, OpenAI statistics 2026: https://www.getpanto.ai/blog/openai-statistics [5] Fewer Better Faster, "Token Prices, Chip Scarcity" (DeepSeek off-peak pricing): https://fewerbetterfaster.substack.com/p/token-prices-chip-scarcity [6] Panto, Anthropic statistics 2026 (Opus pricing): https://www.getpanto.ai/blog/anthropic-ai-statistics [7] http://Gradually.ai, Claude statistics 2026: https://www.gradually.ai/en/claude-statistics/ [8] MarkTechPost, "DeepSeek Open-Sources DeepInfer": https://www.marktechpost.com/2026/10/20/deepseek-deepinfer-open-source-inference-framework/ [9] Latent Space AINews, DeepInfer production figures: https://www.latent.space/p/ainews-deepseek-deepinfer-open-source [10] Traders Agency, Epoch AI 2026 Ascend breakdown: https://tradersagency.com/blog/huawei-pulls-ascend-960dt-forward-to-q1-2027-says-ai-chip-demand-outstrips-its-capacity [11] SemiconductorX, Huawei/HiSilicon HBM constraints: https://semiconductorx.com/spotlight-huawei-hisilicon.html [12] Let's Data Science, V4.1-Flash architecture: https://letsdatascience.com/news/deepseek-updates-flash-model-with-leaner-serving-1cf96356 [13] BigGo Finance, DeepInfer revenue and traffic mix: https://finance.biggo.com/news/538ddce1-7259-43f0-9763-fa6d8949e475 [14] Epoch AI, "Is a compute crunch coming?": https://epoch.ai/gradient-updates/is-a-compute-crunch-coming [15] C114 / Kuai Keji, Chinese API pricing: https://m.c114.com.cn/w16-1307667.html [16] Huawei Central, Ascend 950DT specs: https://www.huaweicentral.com/huawei-ai-chip-three-years-three-major-ai-chip-development/amp/ [17] TechRadar, Ascend 950 vs H200 vs MI300: https://www.techradar.com/pro/huawei-ascend-950-vs-nvidia-h200-vs-amd-mi300-instinct-how-do-they-compare