Compare / DeepSeek-V4.1-Flash-1017 vs GLM-5.3

DeepSeek-V4.1-Flash-1017 vs GLM-5.3

Which is cheaper, which is more capable, and which does better at each kind of work, from 21 results on 3 sources that measured both models.

DeepSeekDeepSeek-V4.1-Flash-1017 Released 17 Oct 2026 · $0.30 in · $1.20 out
Z.aiGLM-5.3 Released 14 Aug 2026 · $1.40 in · $4.40 out
DeepSeek-V4.1-Flash-1017 wins 143 too close to callGLM-5.3 wins 4

Of the 21 results both models have, the better value on each. Results whose reported ranges overlap are too close to call.

Results as of 20 October 2026 (catalogue release 2026-10-20-96eb40c3ec63). See also DeepSeek vs Z.ai, every model from both labs.

DeepSeek-V4.1-Flash-1017 or GLM-5.3? The short answer

Pick DeepSeek-V4.1-Flash-1017: it scores higher (Spring Prompt overall 44 against 36) and costs less.

  • Spring Prompt overall: DeepSeek-V4.1-Flash-1017 44, GLM-5.3 36 (out of 100; how the score works).
  • DeepSeek-V4.1-Flash-1017 is cheaper to run: $0.005 against $0.016 per game of bullet chess on BulletBench (3.3 times less).
  • They score about the same on the Artificial Analysis Intelligence Index (45.1 and 44.8).
  • DeepSeek-V4.1-Flash-1017 writes faster: 212 tokens a second against 87.
  • DeepSeek-V4.1-Flash-1017 is newer: released 17 Oct 2026, against 14 Aug 2026 for GLM-5.3.
  • On our own benchmarks, on the results both models have: DeepSeek-V4.1-Flash-1017 does better for marketing planning.
  • On third-party benchmarks, on the results both models have: DeepSeek-V4.1-Flash-1017 does better for reasoning and knowledge; GLM-5.3 for agents and tool use.

Head to head

44
Spring Prompt overall
36
45.1
Intelligence Index
44.8
$0.52
Price per million tokens, blendedlower is better
$2.15
212
Output speed, tokens a second
87
1,048,576
Context window, tokens
1,048,576

Every fact side by side

DeepSeek-V4.1-Flash-1017GLM-5.3
Price per million tokens$0.30 in · $1.20 out$1.40 in · $4.40 out
Blended (3 in : 1 out)$0.52$2.15
Cheapest host, blended–$0.65 (Novita, FP8)
Cost per game of bullet chess (BulletBench)$0.005$0.016
Cached input, per million$0.006 cached input$0.26 cached input
Intelligence Index45.144.8
Spring Prompt overall4436
Output speed, tokens a second21287
Context window1,048,576 tokens1,048,576 tokens
Released17 Oct 2026 (newer)14 Aug 2026
WeightsOpenOpen
Developer based inChinaChina

Prices are the developer's list price where we have read it, otherwise the typical host on OpenRouter; see every model's price. Intelligence and speed from Artificial Analysis.

Which is better for what

Each model's rank among the models on sale today, for each kind of work, from our own benchmarks and licensed sources. Further right is better; the better rank is in green.

Product listingsTurning a sparse product feed and photos into listings that can go live 21 of 24 not measured
Decks from an analysisTurning a finished analysis into a deck you could present as it is 12 of 24 not measured
User surveysPlanning a user survey and reading its results without being misled 5 of 13 not measured
Marketing planningPlanning a year of ad spend without overspending 11 of 24 21 of 24
Agents and tool useMulti-step tasks with tools: support desks, coding agents, function calls 22 of 168 13 of 168
Professional workReal tasks from banking, consulting and law, business documents and freelance projects not measured 15 of 51
Reasoning and knowledgeHard questions across science, maths and general knowledge 22 of 202 29 of 202
WritingWhat people prefer in blind comparisons, and judged writing quality not measured 24 of 189
Sticking to the factsSummarising without inventing things, and factual answers not measured 54 of 153
Speed under pressureGood decisions against a real clock (fast chess) 21 of 27 25 of 27

From our research

Every shared result

Each model's best result on every measure both have, grouped by benchmark, with the setting that produced it. Under each measure, every model that benchmark has measured is a grey tick, best to the right, so you can see where the two sit in the field. The headline measures of each benchmark come first; the rest are under "Show all". Green marks the better value; where a source reports ranges that overlap, neither is marked.

MeasureDeepSeek-V4.1-Flash-1017GLM-5.3
BulletBench measured by Spring Prompt · 3 results
Cost per game · Bullet 60sUS dollars, lower is better 13 · 22 of 32 measured $0.0047low reasoning $0.0156
Ladder Elo · Bullet 60sladder Elo, higher is better 27 · 29 of 32 measured 147low reasoning 33
Games lost on time · Bullet 60s% of games, lower is better 29 · 28 of 32 measured 87.5%low reasoning 83.3%low reasoning
ROASBench measured by Spring Prompt · 3 results
Overall scorescore out of 100, higher is better 11 · 21 of 24 measured 41.4 24.8
Audience scorescore out of 100, higher is better 9 · 17 of 24 measured 65.3 51.0
Business scorescore out of 100, higher is better 11 · 21 of 24 measured 38.3 12.9
Artificial Analysis reported by Artificial Analysis · 3 results
Artificial Analysis Intelligence Indexindex score, higher is better 16 · 17 of 249 measured 45.1max reasoning 44.8max reasoning
Humanity's Last Exam% of questions, higher is better 27 · 36 of 248 measured 43.3%max reasoning 42.3%max reasoning
Terminal-Bench 4.0% of tasks, higher is better 16 · 11 of 118 measured 33.8%max reasoning 41.9%max reasoning
Show all 21 results (12 more)
MeasureDeepSeek-V4.1-Flash-1017GLM-5.3
BulletBench measured by Spring Prompt · 2 results
Invalid moves · Bullet 60s% of moves, lower is better 1 · 1 of 32 measured 0.0%low reasoning 0.0%
Median move time · Bullet 60smilliseconds, lower is better 31 · 23 of 32 measured 3.3 slow reasoning 1.6 slow reasoning
ROASBench measured by Spring Prompt · 6 results
Consistency scorescore out of 100, higher is better 15 · 20 of 24 measured 20.2 14.8
Contribution profitsimulated US dollars, higher is better 10 · 22 of 24 measured $585,572 $9,718
Cost of a runUS dollars, lower is better 8 · 9 of 24 measured $0.0799 $0.13
Months over budgetmonths of 12, lower is better 1 · 1 of 24 measured 0 0
Planning scorescore out of 100, higher is better 20 · 24 of 24 measured 54.3 51.7
Return on ad spendprofit per $1 spent, higher is better 12 · 22 of 24 measured $0.44 $0.01
Artificial Analysis reported by Artificial Analysis · 4 results
Long-context reasoning (AA-LCR)% of questions, higher is better 19 · 45 of 239 measured 82.7%max reasoning 79.7%max reasoning
Output speedtokens per second, higher is better 15 · 49 of 78 measured 212max reasoning 87.5low reasoning
SciCode% of problems, higher is better 24 · 11 of 119 measured 55.9%max reasoning 59.0%max reasoning
Time to first answer tokenseconds, lower is better 46 · 62 of 78 measured 10.5max reasoning 25.4low reasoning

Quick answers

Is DeepSeek-V4.1-Flash-1017 better than GLM-5.3?

Pick DeepSeek-V4.1-Flash-1017: it scores higher (Spring Prompt overall 44 against 36) and costs less.

Which is cheaper, DeepSeek-V4.1-Flash-1017 or GLM-5.3?

DeepSeek-V4.1-Flash-1017 is cheaper to run: $0.005 against $0.016 per game of bullet chess on BulletBench (3.3 times less).

Which is faster, DeepSeek-V4.1-Flash-1017 or GLM-5.3?

DeepSeek-V4.1-Flash-1017 writes about 212 tokens a second on its usual API, against 87 for GLM-5.3 (Artificial Analysis).

Which is better for marketing planning, DeepSeek-V4.1-Flash-1017 or GLM-5.3?

DeepSeek-V4.1-Flash-1017 ranks 11 of 24 models on sale for planning a year of ad spend without overspending, against 21 for GLM-5.3.

Which is better for agents and tool use, DeepSeek-V4.1-Flash-1017 or GLM-5.3?

GLM-5.3 ranks 13 of 168 models on sale for multi-step tasks with tools: support desks, coding agents, function calls, against 22 for DeepSeek-V4.1-Flash-1017.

Which is better for reasoning and knowledge, DeepSeek-V4.1-Flash-1017 or GLM-5.3?

DeepSeek-V4.1-Flash-1017 ranks 22 of 202 models on sale for hard questions across science, maths and general knowledge, against 29 for GLM-5.3.

Which is better for speed under pressure, DeepSeek-V4.1-Flash-1017 or GLM-5.3?

DeepSeek-V4.1-Flash-1017 ranks 21 of 27 models on sale for good decisions against a real clock (fast chess), against 25 for GLM-5.3.

Run DeepSeek-V4.1-Flash-1017 and GLM-5.3 on your own prompt

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