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GLM-4.7-Flash vs Mercury 2

GLM-4.7-Flash and Mercury 2 are closely matched at 23.8 and 23.7 on the LLM Stats Score. GLM-4.7-Flash is 2.5x cheaper per token.

Zhipu AI · Inception · Updated for 2026

Which is better?

GLM-4.7-Flash and Mercury 2 are closely matched on the overall LLM Stats Score at 23.8 and 23.7.

In the 2 individual benchmarks reported for both models, GLM-4.7-Flash wins 2; this is a narrower head-to-head signal than the composite indexes.

On price, GLM-4.7-Flash is roughly 2.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

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

Choose GLM-4.7-Flash

  • you value its reported benchmark strengths — it wins 2 of 2 exact shared results
  • cost matters — it's about 2.5x cheaper per token
  • you need open weights you can self-host or fine-tune

Choose Mercury 2

  • you want the most recent training data — it shipped Feb 2026

At a glance

The differences that matter most.

GLM-4.7-Flash
Zhipu AI
Mercury 2
Inception
Core performance indexes
LLM Stats Score
23.8
#163
23.7
#164
Reasoning
23.8
#153
22.8
#158
Coding
4.6
#199
12.7
#136
Cost, coverage & limits
Benchmark wins
2 of 2
0 of 2
Input price
$0.07 / M
$0.25 / M
Output price
$0.40 / M
$0.75 / M
Context window
128,000
128,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
GLM-4.7-Flash
Mercury 2
Math
21.2#142
23.5#124
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

6 reported for GLM-4.7-Flash · 6 for Mercury 2

2 shared

GLM-4.7-Flash outperforms in 2 benchmarks (AIME 2025, GPQA), while Mercury 2 is better at 0 benchmarks.

GLM-4.7-Flash significantly outperforms across most benchmarks.

Fri Sep 04 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 3.6x cheaper than Mercury 2 ($0.25/1M tokens).

For output processing, GLM-4.7-Flash ($0.40/1M tokens) is 1.9x cheaper than Mercury 2 ($0.75/1M tokens).

In conclusion, Mercury 2 is more expensive than GLM-4.7-Flash.*

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

Lowest available price from all providers
Fri Sep 04 2026 • llm-stats.com
Zhipu AI
GLM-4.7-Flash
Input tokens$0.07
Output tokens$0.40
Best providerUnknown Organization
Inception
Mercury 2
Input tokens$0.25
Output tokens$0.75
Best providerInception
Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

Both models have the same input context window of 128,000 tokens. GLM-4.7-Flash can generate longer responses up to 16,384 tokens, while Mercury 2 is limited to 8,192 tokens.

Zhipu AI
GLM-4.7-Flash
Input128,000 tokens
Output16,384 tokens
Inception
Mercury 2
Input128,000 tokens
Output8,192 tokens
Fri Sep 04 2026 • llm-stats.com

License

Usage and distribution terms

GLM-4.7-Flash is licensed under MIT, while Mercury 2 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 2

Proprietary

Closed source

Release Timeline

When each model was launched

GLM-4.7-Flash was released on 2026-01-19, while Mercury 2 was released on 2026-02-24.

Mercury 2 is 1 month newer than GLM-4.7-Flash.

GLM-4.7-Flash

Jan 19, 2026

7 months ago

Mercury 2

Feb 24, 2026

6 months ago

1mo 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 2 is available from Inception.

GLM-4.7-Flash

z logo
Unknown Organization
Input Price:Input: $0.07/1MOutput Price:Output: $0.40/1M

Mercury 2

inception logo
Inception
Input Price:Input: $0.25/1MOutput Price:Output: $0.75/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against GLM-4.7-Flash and Mercury 2 side-by-side, then vote on the output you prefer.

GLM-4.7-Flash
✓ Preferred
Mercury 2
Open in Playground

FAQ

Common questions about GLM-4.7-Flash vs Mercury 2.

Which is better, GLM-4.7-Flash or Mercury 2?

GLM-4.7-Flash and Mercury 2 are closely matched on the LLM Stats Score at 23.8 and 23.7. GLM-4.7-Flash is made by Zhipu AI and Mercury 2 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 2 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 2 scores AIME 2025: 91.1%, GPQA: 74.0%, IFBench: 71.0%, LiveCodeBench: 67.0%, Tau2 Airline: 53.0%.

Is GLM-4.7-Flash cheaper than Mercury 2?

GLM-4.7-Flash is 3.6x cheaper for input tokens. GLM-4.7-Flash costs $0.07/M input and $0.40/M output via z. Mercury 2 costs $0.25/M input and $0.75/M output via inception.

What are the context window sizes for GLM-4.7-Flash and Mercury 2?

GLM-4.7-Flash supports 128K tokens and Mercury 2 supports 128K 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 2?

Key differences include LLM Stats Score (23.8 vs 23.7), input pricing ($0.07 vs $0.25/M), licensing (MIT vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-4.7-Flash and Mercury 2?

GLM-4.7-Flash is developed by Zhipu AI and Mercury 2 is developed by Inception.

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