DeepSeek V4 Flash 0731 vs GLM-5.2

Select two models to compare their coding performance, pricing, and features.

Key Takeaways

Coding tier: GLM-5.2 has a higher reference index on the selected shared benchmark configuration than DeepSeek V4 Flash 0731 (100.32 vs 100.00, a 0.32-point difference). This does not by itself establish general coding superiority. Editorial tiers: DeepSeek V4 Flash 0731 = B+; GLM-5.2 = B+. Tiers are separate editorial assessments and do not establish a reliable order within a tier.
API cost estimate: Estimated 1M in / 200K out tokens: $0.7040 (DeepSeek V4 Flash 0731) vs $1.4600 (GLM-5.2).
Metric DeepSeek V4 Flash 0731 GLM-5.2
Coding Index
100.00
100.32
Coding tier B+ B+
Input Price $0.44/1M $0.06/1M
Output Price $1.32/1M $7/1M
Context Window 1.31M 1.05M

Coding Index

Coding Index · Reference baseline: 100

DeepSeek V4 Flash 0731 100.00
GLM-5.2 100.32

Integer index difference: 0.32

DeepSeek V4 Flash 0731 = 100. The index reflects two shared tests, not capability multiples or statistically established gaps.

Verdict

Both models share an editorial tier. The evidence does not establish a reliable order within it; compare them on your own projects.

Capabilities & Use Cases Comparison

DeepSeek V4 Flash 0731 Tier B+

GLM-5.2 Tier B+

Best For
  • •Chinese market
  • •Bilingual development
  • •Budget coding
  • •Web apps
Strengths
  • •Good bilingual coding support
  • •Affordable pricing
  • •Strong in Chinese tech ecosystem
  • •Decent at common coding tasks

DeepSeek V4 Flash 0731

Official · peak 2026-09-07

Off-peak: $0.22 / $0.66 · 1M

Peak: Monday–Friday, UTC 01:00–04:00 and 06:00–10:00; off-peak at other times. Input prices assume a cache miss.

Benchmark evidence and ranking method · DeepSeek V4 Flash 0731

Cross-checked

Artificial Analysis · DeepSeek V4 Flash 0731 (Reasoning, Max Effort)

Test configuration: max

Terminal-Bench 2.1: 78.65% · SciCode: 50.35%

LiveBench · 2026-06-25 · deepseek-v4-flash-0731

Coding: 74.98% · Agentic Coding: 46.77%

ModelRank assigns editorial tiers using public coding evidence, not automatic index thresholds or statistically proven classes. Price, speed, context size and sponsorship do not affect tiers.

DeepSeek V4 Flash 0731 = 100. The index reflects two shared tests, not capability multiples or statistically established gaps.

Results reflect particular model configurations. Agent harnesses, reasoning effort, tools, budgets and tasks may differ. Close indices do not establish superiority. B describes a relative position in this selected group, not an inability to code.

Data checked: 2026-09-10. Snapshot date is the retrieval date, not necessarily the evaluation date.

GLM-5.2

OpenRouter quote 2026-10-11
Benchmark evidence and ranking method · GLM-5.2

Cross-checked

Artificial Analysis · GLM-5.2 (max)

Test configuration: max

Terminal-Bench 2.1: 77.90% · SciCode: 51.16%

LiveBench · 2026-06-25 · glm-5.2

Coding: 79.65% · Agentic Coding: 51.77%

ModelRank assigns editorial tiers using public coding evidence, not automatic index thresholds or statistically proven classes. Price, speed, context size and sponsorship do not affect tiers.

DeepSeek V4 Flash 0731 = 100. The index reflects two shared tests, not capability multiples or statistically established gaps.

Results reflect particular model configurations. Agent harnesses, reasoning effort, tools, budgets and tasks may differ. Close indices do not establish superiority. B describes a relative position in this selected group, not an inability to code.

Data checked: 2026-09-10. Snapshot date is the retrieval date, not necessarily the evaluation date.

Results reflect particular model configurations. Agent harnesses, reasoning effort, tools, budgets and tasks may differ. Close indices do not establish superiority. B describes a relative position in this selected group, not an inability to code.

API cost estimate

1M input + 200K output (USD):

DeepSeek V4 Flash 0731: $0.7040

GLM-5.2: $1.4600

Estimates use the displayed channel and time band; DeepSeek uses peak rates. Cache discounts, tool fees, long-context price tiers and uncounted additional tokens are excluded.

Frequently Asked Questions

Which model is better for coding: DeepSeek V4 Flash 0731 or GLM-5.2?

GLM-5.2 has a higher reference index on the selected shared benchmark configuration than DeepSeek V4 Flash 0731 (100.32 vs 100.00, a 0.32-point difference). This does not by itself establish general coding superiority. Editorial tiers: DeepSeek V4 Flash 0731 = B+; GLM-5.2 = B+. Tiers are separate editorial assessments and do not establish a reliable order within a tier.

How do DeepSeek V4 Flash 0731 and GLM-5.2 compare in API pricing and costs?

DeepSeek V4 Flash 0731: $0.44/1M input, $1.32/1M output (Official · peak); GLM-5.2: $0.06/1M input, $7/1M output (OpenRouter quote). 1M input + 200K output (USD): $0.7040 vs $1.4600.

What are the context window sizes of DeepSeek V4 Flash 0731 and GLM-5.2?

DeepSeek V4 Flash 0731 provides a 1,310,720 token context window, while GLM-5.2 provides 1,048,576 tokens.

Compare current models

DeepSeek V4 Flash 0731 vs DeepSeek V4 Pro 0813 → GLM-5.2 vs DeepSeek V4 Pro 0813 →
Try DeepSeek V4 Flash 0731 → Try GLM-5.2 →