DeepSeek V4.1 Flash vs GLM 5.3
At a Glance
| Compare |  DeepSeek V4.1 FlashDeepSeek |  GLM 5.3Z.ai |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | UnrankedNot in the 46-model eligible cohort | #16 of 4670.4 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 46.9–80.3 |
| CostLower is better · Published-token output estimate | #5 of 44$0.022 per LiveBench case | #34 of 44$0.248 per LiveBench case |
| EfficiencyHigher is better · MM Efficiency v1.5 | UnrankedNot in the 38-model eligible cohort | #26 of 3850.0 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 38.2–54.9 |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.15DeepSeek ↗ · Sep 10, 2026 | $1.20Deepinfra ↗ · Sep 22, 2026 |
| Output priceFrom · USD / 1M tokens | $0.60Deepinfra ↗ · Sep 22, 2026 | $4.00Deepinfra ↗ · Sep 22, 2026 |
| Context windowMaximum documented tokens | 1,049K | 1,000K |
| Model facts checked | Sep 10, 2026View model evidence → | Aug 29, 2026View model evidence → |
Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →
Available Benchmarks
| Benchmark | DeepSeek-V4.1-Flash | GLM-5.3 |
|---|---|---|
| LMArena Agent Arenaagent-2026-09-15-d25aabda0010 · outcome_score · statistical tie | 4.88100% of row best · score · Deepseek V4.1 Flash (Max); 95% CI [3.54852933, 6.21109128]; sessions 20080; observations 2295632; rank 12 | 3.0598% of row best · score · GLM 5.3 (Max); 95% CI [2.43618871, 3.66634458]; sessions 73287; observations 6652488; rank 18 |
| LiveBench2026-06-25 · overall · leader | 83.20100% of row best · percent · deepseek-v4.1-flash-max · 36,355 output tokens / case | 79.1595% of row best · percent · glm-5.3 · 62,090 output tokens / case |
| ToneBench2026-09-11-10-task-4ef099199c9c · overall_score · unverified | 88.03100% of row best · points · DeepSeek V4.1 Flash (max) · 18,199 output tokens / case | 88.34100% of row best · points · GLM-5.3 · 22,204 output tokens / case |
| Overall ResultCounted from the protocol-matched rows above · 1 tie | 1 benchmark winNo overall winner | 0 benchmark winsNo overall winner |
Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.
Quality Versus Estimated Output Cost
Side-by-Side Facts
| Field | DeepSeek-V4.1-Flash | GLM-5.3 |
|---|---|---|
| Developer | DeepSeek | Z.ai |
| Family | Deepseek V4 1 | Glm 5 3 |
| Model | DeepSeek-V4.1-Flash | GLM-5.3 |
| Version | DeepSeek-V4.1-Flash | GLM-5.3 |
| Lifecycle | active | active |
| Released | 2026-09-10 | Unknown |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image | Text |
| Output modalities | Text | Text |
| Context window | 1,049K | 1,000K |
| Total parameters | 763.2B | Unknown |
| Active parameters | Unknown | Unknown |
| License | mit | Unknown |
| Open weights | Yes | No |
| API available | Yes | Yes |
| Self-hostable | Yes | No |
| Provider access | DeepSeek (Standard), Deepinfra (Standard), Together Ai (Standard) | Deepinfra (Standard), Fireworks Ai (Standard), Together Ai (Standard), Z.ai (Standard) |
| Capabilities | agents, chat, fim, generation, reasoning, responses, structured_outputs, tools, vision | agents, chat, reasoning, structured_outputs, tools |
| Architecture design | Causal Encoder-Decoder (20 encoder + 20 decoder layers) | Unknown |
| Backbone parameters | 552000000000 parameters | Unknown |
| Active parameters during decode | 16000000000 parameters | Unknown |
| Active parameters during prefill | 8000000000 parameters | Unknown |
| Pre-training corpus | 45000000000000 tokens | Unknown |
| Reasoning effort range | 1–100 | Unknown |
| Routed experts per MoE layer | 384 experts | Unknown |
| Routed experts per token | 6 experts | Unknown |
| Transformer layers | 40 layers | Unknown |
DeepSeek V4.1 Flash Capabilities
GLM 5.3 Capabilities
Related Comparisons
All text comparisons →| A | Pair | B | Context |
|---|---|---|---|
DeepSeek-V4-FlashDeepSeek | vs | DeepSeek-V4.1-FlashDeepSeek | family variantstext |
DeepSeek-V4.1-FlashDeepSeek | vs | GLM-5.2Z.ai | cross-developer peerstext |
DeepSeek-V4.1-FlashDeepSeek | vs |  GPT-6 AstraOpenAI | cross-developer peersimage, text |
Claude Fable 5.1Anthropic | vs | DeepSeek-V4.1-FlashDeepSeek | cross-developer peersimage, text |
DeepSeek-V4.1-FlashDeepSeek | vs |  Gemini 3.1 ProGoogle DeepMind | cross-developer peerstext |
DeepSeek-V4.1-FlashDeepSeek | vs | Grok 4.6xAI | cross-developer peersimage, text |
DeepSeek-V4.1-FlashDeepSeek | vs |  Qwen3.8-MaxQwen | cross-developer peersimage, text |
DeepSeek-V4.1-FlashDeepSeek | vs |  Kimi-K3Moonshot AI | cross-developer peersimage, text |
 MiniMax-M3MiniMax | vs | DeepSeek-V4.1-FlashDeepSeek | cross-developer peersimage, text |
DeepSeek-V4.1-FlashDeepSeek | vs |  Hy4 previewTencent | cross-developer peerstext |
Seed 2.1 ProByteDance Seed | vs | DeepSeek-V4.1-FlashDeepSeek | cross-developer peersimage, text |
DeepSeek-V4.1-FlashDeepSeek | vs |  Mistral Large 3Mistral AI | cross-developer peersimage, text |
Primary Evidence
Sources and Freshness
Questions
DeepSeek V4.1 Flash vs GLM 5.3 FAQs
Is DeepSeek V4.1 Flash or GLM 5.3 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both DeepSeek V4.1 Flash and GLM 5.3, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, DeepSeek V4.1 Flash or GLM 5.3?+
DeepSeek V4.1 Flash is $0.15 and GLM 5.3 is $1.20 per million tokens, so DeepSeek V4.1 Flash is cheaper on this metric. DeepSeek V4.1 Flash is $0.60 and GLM 5.3 is $4.00 per million tokens, so DeepSeek V4.1 Flash is cheaper on this metric.
Which has a larger context window, DeepSeek V4.1 Flash or GLM 5.3?+
DeepSeek V4.1 Flash has the larger sourced context window. DeepSeek V4.1 Flash supports 1,049K and GLM 5.3 supports 1,000K.
Which performs better in benchmarks, DeepSeek V4.1 Flash or GLM 5.3?+
There is no overall benchmark winner: An overall winner requires at least two decisive benchmarks from at least two original publishers.
Can DeepSeek V4.1 Flash or GLM 5.3 be self-hosted?+
DeepSeek V4.1 Flash is the only model in this pair currently marked as self-hostable. DeepSeek V4.1 Flash is open weight; GLM 5.3 is not marked open weight.
Can DeepSeek V4.1 Flash and GLM 5.3 understand images?+
DeepSeek V4.1 Flash is documented with image input; GLM 5.3 is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, DeepSeek V4.1 Flash or GLM 5.3?+
DeepSeek V4.1 Flash has the larger sourced maximum output: DeepSeek V4.1 Flash supports 393K and GLM 5.3 supports 131K output tokens.
Do DeepSeek V4.1 Flash and GLM 5.3 support reasoning and tool use?+
DeepSeek V4.1 Flash: reasoning, tool calling, and image input. GLM 5.3: reasoning and tool calling. Feature support does not establish relative quality.
Which is available from more inference providers, DeepSeek V4.1 Flash or GLM 5.3?+
DeepSeek V4.1 Flash has 3 sourced provider routes; GLM 5.3 has 4, so GLM 5.3 has broader tracked availability.
Which offers better value, DeepSeek V4.1 Flash or GLM 5.3?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.