--- title: "Z.ai: GLM 4.7 Flash — price, capability and what beats it · Undominated.ai" canonical: https://undominated.ai/models/z-ai__glm-4.7-flash/ description: "Z.ai: GLM 4.7 Flash: $0.060/M in, $0.400/M out. Independent capability scores, and alternatives compared under recorded workload and capability requirements." --- # Z.ai: GLM 4.7 Flash — price, capability and what beats it · Undominated.ai > Z.ai: GLM 4.7 Flash: $0.060/M in, $0.400/M out. Independent capability scores, and alternatives compared under recorded workload and capability requirements. [Check base rates for this workload](/check/z-ai__glm-4.7-flash/) [Cheaper alternatives](/alternatives/z-ai__glm-4.7-flash/) [Family](/families/glm/) [Compare models](https://undominated.ai/compare/?models=z-ai%2Fglm-4.7-flash) Comparison context Choose up to three standard models in Compare. Requirements and prompt length apply in Compare. This page keeps its stated price basis and workload controls. MODEL PROOF # GLM 4.7 Flash Z.ai · 19 Jan 2026 Balanced Summarise Chat Code gen Agentic BETTER VALUE OPTION ## A stored alternative has an equal-or-higher measured score and an equal-or-lower price. **$0.145** / 1M tokens Balanced · 3 tokens in per 1 out Serving precision differs between offers. [Gemma 4 26B A4B](/models/google__gemma-4-26b-a4b-it/) · Δ score 83 points · 13% lower measured price · $0.127 / 1M tokens [Qwen3.5-Flash](/models/qwen__qwen3.5-flash-02-23/) is a further stored option with these losses: 118K → 66K max output Evidence as of 06 Oct 2026 [openrouter/models](https://openrouter.ai/api/v1/models) [LMArena · cc-by-4.0](https://huggingface.co/datasets/lmarena-ai/leaderboard-dataset) Independent LMArena score 1,350.9 ± 5.68 · 11,977 votes Context window 200K Maximum output 117.96K Input modalities text Output modalities text Published input price $0.060 / 1M tokens Published output price $0.400 / 1M tokens Pricing kind fixed Inspect [complete billing conditions](#billing-details) and endpoint terms below. Price from Venice: the cheapest offer that is serving, at standard delivery and at a declared precision that is not 4-bit (fp8), at its standard rate. The maker’s own precision is not known. Every price dimension · USD per million tokens | Input | $0.060 /M | | --- | --- | | Output | $0.400 /M | | Cached input | $0.010 /M | | Cache write | Unknown /M | | Cache write 1h | Unknown /M | | Reasoning | Unknown /M | ### Who sells it The same weights, different shops. Cheapest is not like-for-like when serving precision differs. Headline cheapest is a lower precision. Like-for-like at the best declared precision is $0.060/M from Venice. 3 provider offers · rates, limits and conditions Rates are USD per million tokens. Endpoint terms can differ even when the quoted price and precision match. A listed parameter is a provider declaration, not a task-success test. | Seller | Input | Output | Precision | Uptime (1d) | | --- | --- | --- | --- | --- | | Seller Venice venice/fp8 Endpoint terms Cached input /M $0.010 Context limit 128,000 tokens Output limit 16,384 tokens Tools Listed by endpoint Reasoning Listed by endpoint Promotional discount None reported Uptime · last 30 minutes 97.68% | Input $0.060 | Output $0.400 | Precision fp8 | Uptime (1d) 98.13% | | Seller Cloudflare cloudflare Endpoint terms Cached input /M Unknown Context limit 131,072 tokens Output limit 117,964 tokens Tools Listed by endpoint Reasoning Listed by endpoint Promotional discount None reported Uptime · last 30 minutes 99.67% | Input $0.061 | Output $0.400 | Precision undeclared | Uptime (1d) 99.32% | | Seller Novita novita/bf16 Endpoint terms Cached input /M $0.010 Context limit 200,000 tokens Output limit 128,000 tokens Tools Listed by endpoint Reasoning Listed by endpoint Promotional discount None reported Uptime · last 30 minutes 82.60% | Input $0.070 | Output $0.400 | Precision bf16 | Uptime (1d) 87.74% | ### Independent scores | LMArena Elo | 1350.9 default | | --- | --- | LMArena Elo under CC BY 4.0. Absence of another board is not a score of zero. #### Best rankings by task - UI components #49 1214 - Websites #57 1201 - Code categories #59 1183 - Game development #72 1148 - 3D #73 1128 - SVG #75 1037 - Data visualisation #86 1130 Per-task Elo and rank from [Design Arena](https://designarena.ai), via OpenRouter’s model feed. The rank is the feed’s, and it counts models OpenRouter does not list. ### Capability | Context window | 200K | | --- | --- | | Max output | 117K | | Input modes | text | | Tool use | yes | | Reasoning | optional | | Open weights | Unknown | ### Provenance | Price source | [openrouter.ai](https://openrouter.ai/api/v1/models) | | --- | --- | | Fetched | 2026-10-06 | | Quality data | verified | As a 30B-class SOTA model, GLM-4.7-Flash offers a new option that balances performance and efficiency. It is further optimized for agentic coding use cases, strengthening coding capabilities, long-horizon task planning,... ## Questions this page answers What does GLM 4.7 Flash cost? $0.060/M in, $0.400/M out in this catalogue, as of the fetch date on this page. That is the API row, not a subscription. Does GLM 4.7 Flash have an independent quality score? GLM 4.7 Flash has an LMArena score in this catalogue. What beats GLM 4.7 Flash? Gemma 4 26B A4B has an equal-or-higher measured score and an equal-or-lower price. Does this page use Artificial Analysis scores for GLM 4.7 Flash? No. Artificial Analysis figures are not published here. Quality on this page is LMArena Elo where a score exists; otherwise the row is unrated. Is the cheapest GLM 4.7 Flash endpoint the same product? Headline cheapest is a lower precision. Like-for-like at the best declared precision is $0.060/M from Venice. MODEL MONUMENT ## Save or share this proof Download proof card · 1200 × 630 Preview and more sharing options Z.ai: GLM 4.7 Flash. Balanced workload. Better value option available. Evidence as of 06 Oct 2026. Copy model link Download square card · 1080 × 1080 Copy landscape image Share landscape card ## Related - Both better and cheaper [Gemma 4 26B A4B](/models/google__gemma-4-26b-a4b-it/) - Higher score and cheaper, with a named trade [Qwen3.5-Flash](/models/qwen__qwen3.5-flash-02-23/) - Nearby on the capability axis [o4 Mini](/models/openai__o4-mini/) - Same vendor [GLM 4.5V](/models/z-ai__glm-4.5v/) - Z.ai models [Z.ai](/providers/z-ai/) - Where this model appears [spreads](/spreads/) - Nearby on the capability axis [MiniMax M1](/models/minimax__minimax-m1/) - Same vendor [GLM 4.6V](/models/z-ai__glm-4.6v/) - Where this model appears [traps](/traps/) - Nearby on the capability axis [Mercury 2](/models/inception__mercury-2/) - Same vendor [GLM 4.5 Air](/models/z-ai__glm-4.5-air/) - Where this model appears [significance](/significance/) ## Badge The verdict as one SVG, for a README or a docs page. It states this model's dominance status at the balanced workload on the LMArena lens, with the date it was computed, and it is rebuilt with the catalogue — so it changes when the verdict changes, including to one you would rather it did not. Markdown Copy [![GLM 4.7 Flash — Undominated.ai dominance verdict](https://undominated.ai/badge/z-ai__glm-4.7-flash.svg)](https://undominated.ai/models/z-ai__glm-4.7-flash/) HTML Copy GLM 4.7 Flash — Undominated.ai dominance verdict Direct file: [https://undominated.ai/badge/z-ai__glm-4.7-flash.svg](https://undominated.ai/badge/z-ai__glm-4.7-flash.svg) — a static SVG, written by scripts/build-badges.mjs on every build, so the copy you embed is never older than the last deploy. ## Continue your investigation - [Explore model families](/families/) - [Compare a shortlist](/compare/) - [Check a model](/check/) - [Understand the evidence](/methodology/)