
DeepSeek V4 Flash vs GLM-5.2: Cheap Agentic Coder vs Open-Weight Coding Model
- OrcaNEWOrca: OrcaCyber Zero 1.02026-09-17$3.00 / $5.00 per 1M tokens
- orcaNEWOrca: OrcaVerify Text 1.02026-09-16$2.00 / $0.00 per 1M tokens
- deepseekNEWDeepSeek: DeepSeek V4.1 Flash2026-09-1040Intelligence
- openaiOpenAI: GPT-6 Astra2026-09-0453Intelligence77Coding
- googleGoogle: Gemini 3.8 Flash2026-09-0241Intelligence76Coding
- qwenQwen: Qwen3.8 Max (0902)2026-09-0245Intelligence76Coding
- anthropicAnthropic: Claude Fable 5.12026-09-0153Intelligence82Coding
- AlibabaQwen: Qwen3.8 Flash2026-08-26$0.15 / $0.47 per 1M tokens
- z-aiZ.ai: GLM 5.3 Flash2026-08-2642Intelligence72Coding
- DeepSeekDeepSeek: DeepSeek V4 Flash Vision (Exp)2026-08-21$0.22 / $0.66 per 1M tokens
- z-aiZ.ai: GLM 5.32026-08-1845Intelligence75Coding
- obsidianQwen3.8 27B2026-08-1534Intelligence68Coding
- deepseekDeepSeek: DeepSeek V4 Pro 08132026-08-1236Intelligence69Coding
- grokSpaceXAI: Grok 4.62026-08-1244Intelligence77Coding
- metaMeta: Muse Spark 1.22026-08-0540Intelligence72Coding
- qwenQwen: Qwen3.8 Max2026-08-0345Intelligence76Coding
- deepseekDeepSeek: DeepSeek V4 Flash 07312026-07-3134Intelligence69Coding
- minimaxMiniMax: MiniMax-H32026-07-31minimax/minimax-h3
- qwenQwen: Qwen3.7 Flash2026-07-27$0.03 / $0.13 per 1M tokens
- orcaOrcaDub: OrcaDub 1.02026-07-27orca/dub
Two of China's strongest cost-efficient models square off: DeepSeek V4 Flash, freshly upgraded for agents and coding, and GLM-5.2 from Zhipu, a top open-weight coding model under an MIT license. Both are cheap, both are coding-focused, and both offer 1M-token contexts — so the choice comes down to openness, exact capability, and price. Figures are labeled by source.
Accuracy note: V4 Flash's scores are DeepSeek-reported (official change log, 2026-07-31); GLM-5.2's are Zhipu vendor-reported; pricing is from OrcaRouter's pass-through pages. Vendor-harness numbers run optimistic — verify on your own tasks.
TL;DR. V4 Flash ($0.15 / $0.29) is a 284B / 13B-active MoE tuned for agents and coding (Terminal-Bench 2.1 82.7, DeepSeek-reported), text-only, accessed via API. GLM-5.2 (~$1.20 / $4.10) is a 753B MoE, MIT-licensed and self-hostable, strong on coding (SWE-bench Pro 62.1%, vendor-reported). Flash is much cheaper via API and agent-tuned; GLM-5.2 wins if you need open weights to own and self-host. Both carry 1M contexts.
Key takeaways
• Price (API): Flash ~$0.15 / $0.29 is far cheaper than GLM-5.2's ~$1.20 / $4.10 hosted rate.
• Openness: GLM-5.2 is MIT open-weight and self-hostable; V4 Flash is accessed via API.
• Both are coding-focused with 1M contexts; Flash adds native Codex/Responses-API agent support.
• Flash is text-only and agent-tuned; GLM-5.2 is a versatile open coder you can fine-tune.
• Both on OrcaRouter at 0% markup for easy comparison; GLM-5.2 can also be self-hosted.
What each model is
V4 Flash is DeepSeek's efficiency tier: 284B / 13B-active MoE, 1M context, up to 384K output, text-only, reasoning/tools/JSON, post-trained (build -0731) for agents and coding with native Responses-API and Codex support, at ~$0.15 / $0.29. GLM-5.2 is Zhipu's June 2026 open-weight flagship: a ~753B MoE (about 40B active), MIT-licensed and self-hostable, 1M-token context, tuned for coding and agents, at roughly $1.20 / $4.10 per million tokens via hosted providers.

Coding and agents
Both are coding specialists, reported through their own harnesses. V4 Flash's -0731 build posts Terminal-Bench 2.1 82.7, Toolathlon (verified) 70.3, and DSBench-FullStack 68.7 (DeepSeek-reported), and it's Codex-adapted. GLM-5.2 posts SWE-bench Pro 62.1% and Terminal-Bench 2.1 81.0% (Zhipu-reported), and is a proven open-weight coder with a growing ecosystem. Head-to-head is hard to call from vendor numbers alone — both look strong on agentic coding — so the decision usually rests on openness and price rather than a benchmark tie-breaker. Test both on your own repositories.
Openness: GLM's distinctive edge
The biggest structural difference is licensing. GLM-5.2 ships under MIT open weights, so you can download, fine-tune, air-gap, and self-host it — valuable for data-control, customization, and avoiding platform dependence. V4 Flash is consumed via API (DeepSeek or a router). If owning and self-hosting the model matters, GLM-5.2 is the pick; if you're happy consuming a cheap API, Flash's lower price and agent tuning win.
Price
Via API, Flash is dramatically cheaper — ~$0.15 / $0.29 versus GLM-5.2's ~$1.20 / $4.10 hosted rate (roughly 8x lower on input, 14x on output). GLM-5.2's counter is that its open weights can be free to self-host (compute aside), which changes the economics if you have infrastructure. So: for cheapest hosted usage, Flash; for owned, amortized self-hosting, GLM-5.2 can compete.

Which should you choose?
Choose DeepSeek V4 Flash if…
You want the cheapest hosted coding/agent API, native Codex/Responses-API support, and a 1M context, and you don't need to own the weights.
Choose GLM-5.2 if…
You need MIT open weights to self-host, fine-tune, or air-gap, and you value a proven open coder — accepting a higher hosted price or bringing your own compute.
Compare both through one endpoint
Both are on OrcaRouter at 0% markup through one OpenAI-compatible endpoint, so you can benchmark V4 Flash against GLM-5.2 on your real coding prompts and route by cost or capability — while keeping the option to self-host GLM-5.2 where openness matters.

FAQ
Is V4 Flash cheaper than GLM-5.2?
Via API, yes — dramatically: ~$0.15 / $0.29 versus ~$1.20 / $4.10. GLM-5.2's open weights can be cheaper if you self-host at scale.
Which is open-weight?
GLM-5.2 (MIT, self-hostable). V4 Flash is accessed via API.
Which is better for coding?
Both are strong coders by their own benchmarks (Flash: Terminal-Bench 2.1 82.7; GLM-5.2: SWE-bench Pro 62.1%). Test on your own code.
Do both have 1M context?
Yes — both offer a 1M-token context.
Can I use both?
Yes — via OrcaRouter's endpoint, and self-host GLM-5.2 where you need open weights.
Bottom line
V4 Flash vs GLM-5.2 is cheap agent-tuned API versus open-weight ownership. Flash is far cheaper to call and freshly tuned for coding agents; GLM-5.2 gives you MIT open weights to own, fine-tune, and self-host. Both are strong 1M-context coders — so choose on openness and price, and use OrcaRouter to compare them side by side before you commit.
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