GLM-4.7-Flash vs Mercury 3

Mercury 3 leads the LLM Stats Score 36.1 to 23.0. GLM-4.7-Flash is 1.1x cheaper per token.

Zhipu AI · Inception · Updated for 2026

Which is better?

Mercury 3 leads the overall LLM Stats Score 36.1 to 23.0, ranking #98 overall.

In the 1 individual benchmarks reported for both models, Mercury 3 wins 1; this is a narrower head-to-head signal than the composite indexes.

On price, GLM-4.7-Flash is roughly 1.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Mercury 3 also accepts a larger context window (1,000,000 input tokens), making it the stronger choice for long documents and large codebases.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose GLM-4.7-Flash

cost matters — it's about 1.1x cheaper per token
you need open weights you can self-host or fine-tune

Choose Mercury 3

overall performance matters — it scores 36.1 and ranks #98 on LLM Stats
your work emphasizes reasoning and coding — it leads those capability indexes
you value its reported benchmark strengths — it wins 1 of 1 exact shared results
you process long inputs — it offers a 1,000,000 token context window
you want the most recent training data — it shipped Oct 2026

At a glance

The differences that matter most.

Better token value: GLM-4.7-Flash

Core performance indexes

LLM Stats Score

23.0

#201 · 6 evals

36.1

#98 · 10 evals

Best

Reasoning

23.0

#189 · 6 evals

34.8

#103 · 8 evals

Best

Coding

3.7

#237 · 1 evals

21.5

#105 · 1 evals

Best

Agents

4.1

#180 · 2 evals

19.4

#84 · 4 evals

Best

Cost, coverage & limits

Benchmark wins

0 of 1

1 of 1

Best

Input price

$0.07 / M

Best

$0.10 / M

Output price

$0.40 / M

$0.35 / M

Best

Context window

128,000

1,000,000

Best

Individual benchmarks

6 reported for GLM-4.7-Flash · 12 for Mercury 3

1 shared

GLM-4.7-Flash outperforms in 0 benchmarks, while Mercury 3 is better at 1 benchmark (GPQA).

Mercury 3 significantly outperforms across most benchmarks.

Thu Oct 22 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

GLM-4.7-Flash costs less

For input processing, GLM-4.7-Flash ($0.07/1M tokens) is 1.4x cheaper than Mercury 3 ($0.10/1M tokens).

For output processing, GLM-4.7-Flash ($0.40/1M tokens) is 1.1x more expensive than Mercury 3 ($0.35/1M tokens).

In conclusion, Mercury 3 is more expensive than GLM-4.7-Flash.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers

Thu Oct 22 2026 • llm-stats.com

GLM-4.7-Flash

Input tokens$0.07

Output tokens$0.40

Best providerUnknown Organization

Mercury 3

Input tokens$0.10

Output tokens$0.35

Best providerInception

Notice missing or incorrect data?

Context Window

Maximum input and output token capacity

Mercury 3 accepts 1,000,000 input tokens compared to GLM-4.7-Flash's 128,000 tokens. Mercury 3 can generate longer responses up to 131,072 tokens, while GLM-4.7-Flash is limited to 16,384 tokens.

GLM-4.7-Flash

Input128,000 tokens

Output16,384 tokens

Mercury 3

Input1,000,000 tokens

Output131,072 tokens

Thu Oct 22 2026 • llm-stats.com

License

Usage and distribution terms

GLM-4.7-Flash is licensed under MIT, while Mercury 3 uses a proprietary license.

License differences may affect how you can use these models in commercial or open-source projects.

GLM-4.7-Flash

MIT

Open weights

Mercury 3

Proprietary

Closed source

Release Timeline

When each model was launched

GLM-4.7-Flash was released on 2026-01-19, while Mercury 3 was released on 2026-10-19.

Mercury 3 is 9 months newer than GLM-4.7-Flash.

GLM-4.7-Flash

Jan 19, 2026

9 months ago

Mercury 3

Oct 19, 2026

3 days ago

9mo newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Provider Availability

GLM-4.7-Flash is available from ZAI. Mercury 3 is available from Inception.

GLM-4.7-Flash

Unknown Organization

Input Price:Input: $0.07/1MOutput Price:Output: $0.40/1M

Mercury 3

Inception

Input Price:Input: $0.10/1MOutput Price:Output: $0.35/1M

* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against GLM-4.7-Flash and Mercury 3 side-by-side, then vote on the output you prefer.

GLM-4.7-Flash

✓ Preferred

Mercury 3

Open in Playground

FAQ

Common questions about GLM-4.7-Flash vs Mercury 3.

Which is better, GLM-4.7-Flash or Mercury 3?

Mercury 3 leads the LLM Stats Score 36.1 to 23.0. GLM-4.7-Flash is made by Zhipu AI and Mercury 3 is made by Inception. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does GLM-4.7-Flash compare to Mercury 3 in benchmarks?

GLM-4.7-Flash scores AIME 2025: 91.6%, Tau-bench: 79.5%, GPQA: 75.2%, SWE-Bench Verified: 59.2%, BrowseComp: 42.8%. Mercury 3 scores GPQA: 89.2%, AA-LCR: 77.7%, IFBench: 76.8%, MRCR v2: 75.5%, DeepSearchQA: 71.3%.

Is GLM-4.7-Flash cheaper than Mercury 3?

GLM-4.7-Flash is 1.4x cheaper for input tokens. GLM-4.7-Flash costs $0.07/M input and $0.40/M output via z. Mercury 3 costs $0.10/M input and $0.35/M output via inception.

What are the context window sizes for GLM-4.7-Flash and Mercury 3?

GLM-4.7-Flash supports 128K tokens and Mercury 3 supports 1.0M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between GLM-4.7-Flash and Mercury 3?

Key differences include LLM Stats Score (23.0 vs 36.1), context window (128K vs 1.0M), input pricing ($0.07 vs $0.10/M), licensing (MIT vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-4.7-Flash and Mercury 3?

GLM-4.7-Flash is developed by Zhipu AI and Mercury 3 is developed by Inception.

GLM-4.7-Flash vs Mercury 3