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- GPT-6 Sol vs. GLM-5.3-Flash
OpenAIZ.aiLLM matchup
GPT-6 Solvs.GLM-5.3-Flash
Which one is better?
GPT-6 Sol performs better than GLM-5.3-Flash, but costs 13.3 times (input) and 20 times (output) as much.
GPT-6 Sol
Rank 13
GLM-5.3-Flash
Rank 37
GPT-6 Sol
GLM-5.3-Flash
GPT-6 Sol
GLM-5.3-Flash
GPT-6 Sol
Rank 3 of 785
GLM-5.3-Flash
Rank 202 of 785
Above 272,000 tokens of context, GPT-6 Sol costs more: $4 input and $15 output per 1M tokens.
Choose GPT-6 Sol for
Choose GLM-5.3-Flash for
No clear advantage
On this page
Where is the difference?
Strengths at a glance
GPT-6 SolGLM-5.3-FlashMedian of all ranked models
95 % range: GPT-6 Sol 112.2 to 117.6, GLM-5.3-Flash 91.3 to 102.2.
The same values and verdicts as the bars below. In the close-up the net starts at 80 points, just below the weaker model's lowest value; the reference group average is 100. Not in the net because a model has no own value there or the data are too thin: Legal, Health.
GPT-6 Sol is ahead in 7 of 10 areas, GLM-5.3-Flash in none.
GPT-6 Sol ahead: 7level: 1too little data: 2
Bar length shows the gap in index points (full width 15 points, one standard deviation of the reference group). Solid means clearly ahead, hatched not certain yet, a thin grey bar level.
Show 4 more areas that do not count toward the overall index
Bar length shows the gap in index points (full width 15 points, one standard deviation of the reference group). Solid means clearly ahead, hatched not certain yet, a thin grey bar level.
GPT-6 Sol vs. GLM-5.3-Flash at the same effort
Both models measured at the same reasoning efforts. This shows whether a lead comes from the model or only from more compute.
| Effort | GPT-6 Sol | GLM-5.3-Flash | Gap | Verdict | Test series |
|---|---|---|---|---|---|
| max | 110.5 | 94.2 | 15.1 | GPT-6 Sol ahead | 11 |
| Overall index (max vs. max) | 110.5 | 94.2 | 16.4 | GPT-6 Sol ahead |
Gap and verdict compare only the Artificial Analysis test series in which both models are measured at that effort. Tied below 3 points, ahead only beyond two standard errors. The single values rest on all test series of each model, so their difference can deviate from the gap.
Which model for which task?
Everyday tasks, translated from the area values above. Each row names the values it rests on.
See for yourself: same task, one attempt
The same prompt for both models. We show the latest attempt without fixes; it does not count toward the overall index.
GPT-6 Sol

Oct 1, 2026 · 80 s · $0.04
Test details
- Run date
- Oct 1, 2026
- API provider
- openrouter
- Requested API model
- openai/gpt-6-sol
- Reasoning setting
- high
- Token limit including reasoning
- 8,192 tokens
- Output tokens
- 4,389 tokens
- Cost of the attempt
- $0.0439
- Response time
- 80.5 s
- API model reported in response
- openai/gpt-6-sol
- Pinned endpoint
- OpenAI | openai/gpt-6-sol-20260922
- Temperature
- Provider default
- Test protocol
- community-visual-tests-v1
- Technical checks
- Passed, not a quality rating
Visually reviewed. This individual test does not establish overall model quality.
GLM-5.3-Flash

Oct 1, 2026 · 50 s · $0.0013
Test details
- Run date
- Oct 1, 2026
- API provider
- openrouter
- Requested API model
- z-ai/glm-5.3-flash
- Reasoning setting
- high
- Token limit including reasoning
- 8,192 tokens
- Output tokens
- 2,563 tokens
- Cost of the attempt
- $0.0013
- Response time
- 49.7 s
- API model reported in response
- z-ai/glm-5.3-flash
- Pinned endpoint
- Z.AI | z-ai/glm-5.3-flash-20260826
- Temperature
- Provider default
- Test protocol
- community-visual-tests-v1
- Technical checks
- Passed, not a quality rating
Visually reviewed. This individual test does not establish overall model quality.
Earlier attempts (1)
- Sep 7, 2026API request failedReasoning setting: high
SVG short test
SVG short test
One SVG task with the same fixed settings for every model, without hidden thinking.
Prompt
Return only one standalone SVG of a pelican riding a bicycle. Use viewBox="0 0 800 600", simple shapes, two clearly visible wheels and a recognizable pelican with a long beak. At most 30 SVG elements and 1800 characters. No Markdown, explanations, comments, scripts, animation, CSS or external resources.
GPT-6 Sol
Unavailable in this round
GLM-5.3-Flash
Unavailable in this round
GPT-6 Sol and GLM-5.3-Flash in the overall index
Every model with a place in the overall index, both models of this matchup highlighted. You can add or hide other models.
Overall index (Gradually Meta-Score v4)
20 of 92 models
4 models in this view are measured at a lower reasoning effort than max in the overall index. Dashed column: lower reasoning effort than the top.
Popularity compared
How often the models are searched for, used and mentioned, on a scale from 0 to 100.
GPT-6 Sol is more popular than GLM-5.3-Flash: 73 to 44 out of 100.
Over time
Weekly values from October 18, 2026 to November 7, 2026
GPT-6 SolGLM-5.3-Flash
All data side by side
The better value is bold. For the overall index only when the gap is clear.
| Metric | GPT-6 Sol | GLM-5.3-Flash |
|---|---|---|
| Intelligence | ||
| Overall indexpoints, 100 = reference group average, higher is better | 110.5 | 94.2 |
| Rank | Rank 13 of 92 | Rank 37 of 92 |
| Price per 1M tokens | ||
| Inputwhat you send | $2above 272,000 tokens: $4 | $0.15 |
| Outputwhat the model writes | $10above 272,000 tokens: $15 | $0.50 |
| Cost per task (own tests)average of 3 original-protocol tasks both models passed (SVG short test not included) | $0.044 | $0.005 |
| Speed | ||
| Tokens per second | 111 | 56 |
| Popularity | ||
| Popularitysearch, usage and mentions, 0 to 100 | 73Rank 3 of 785 | 44Rank 202 of 785 |
| Technical | ||
| Context windowhow much text the model reads at once | 1.05 M tokens≈ 1,580 A4 pages | 1 M tokens≈ 1,500 A4 pages |
| Knowledge cutoff | Apr 20, 2026 | n/a |
| Released | Sep 22, 2026 | Aug 26, 2026 |
| Availability | Active | Open Source |
| Open weights | no | yes |
Prices without caching or batch discounts · Page count as a rule of thumb from Artificial Analysis
Is there a better choice?
Overall index 119.2, rank 7$2 input and $10 output per 1M tokens
GLM-5.3-Flash vs. GPT-6.1 SolOverall index 103.4, rank 20$0.10 input and $0.50 output per 1M tokens
GPT-6 Sol vs. Claude Haiku 5.5Overall index 126.1, rank 1$4 input and $20 output per 1M tokens
GPT-6 Sol vs. Claude Opus 5.5Shared benchmarks
Single results from the same benchmark version, task and metric. A value is bold only with the same test setup and a clear gap.
A: GPT-6 SolB: GLM-5.3-Flash
Show 54 more benchmarks
More comparisons
Compare GPT-6 Sol and GLM-5.3-Flash with the models people compare them with most often.
Compare another matchup
Predecessor and successor
The most popular comparisons
- 1GPT-6 Sol vs. GPT-5.6 Sol
- 2GPT-6 Sol vs. DeepSeek-V4.1-Flash
- 3Claude Opus 5.5 vs. GLM-5.3-Flash
- 4GPT-6 Sol vs. Gemini 3.8 Flash
- 5GPT-6 Luna vs. GLM-5.3-Flash
- 6GPT-6 Sol vs. GPT-5.6 Terra
- 7Gemini 3.8 Flash vs. GLM-5.3-Flash
- 8DeepSeek V4.1 Flash 1017 vs. GLM-5.3-Flash
- 9Grok 4.7 vs. GLM-5.3-Flash
Show all 66 comparisons
- 10GPT-6 Astra vs. GPT-6 Sol
- 11GPT-6.1 Sol vs. GLM-5.3-Flash
- 12DeepSeek-V4.1-Flash vs. GLM-5.3-Flash
- 13GPT-5.4 vs. GLM-5.3-Flash
- 14Claude Sonnet 4.6 vs. GLM-5.3-Flash
- 15Claude Opus 5 vs. GLM-5.3-Flash
- 16DeepSeek-V4-Flash vs. GLM-5.3-Flash
- 17Claude Sonnet 5.5 vs. GPT-6 Sol
- 18GLM-5.3-Flash vs. Mistral Large 4
- 19GLM-5.3-Flash vs. GLM-5.3
- 20GPT-6 Sol vs. Gemini 3.1 Pro Preview
- 21Claude Opus 4.8 vs. GPT-6 Sol
- 22GPT-6 Astra vs. GLM-5.3-Flash
- 23Claude Haiku 5.5 vs. GLM-5.3-Flash
- 24GPT-6 Sol vs. GPT-5.4
- 25GPT-5.6 Sol vs. GLM-5.3-Flash
- 26GPT-6 Sol vs. DeepSeek V4.1 Flash 1017
- 27GPT-6 Sol vs. Qwen 3.8 27B
- 28GPT-6 Sol vs. GPT-6 Luna
- 29Claude Opus 4.6 vs. GLM-5.3-Flash
- 30GPT-6 Sol vs. Kimi K3.1 Pro
- 31Claude Sonnet 4.6 vs. GPT-6 Sol
- 32Claude Opus 4.8 vs. GLM-5.3-Flash
- 33Kimi K3 vs. GLM-5.3-Flash
- 34GPT-6 Sol vs. Grok 4.7
- 35Claude Haiku 5.5 vs. GPT-6 Sol
- 36Claude Opus 5.5 vs. GPT-6 Sol
- 37Claude Haiku 4.5 vs. GLM-5.3-Flash
- 38GPT-6 Sol vs. Qwen 3.8 Max 0902
- 39Claude Sonnet 5 vs. GPT-6 Sol
- 40GPT-6 Sol vs. Kimi K3
- 41Claude Fable 5.1 vs. GPT-6 Sol
- 42GPT-6 Sol vs. DeepSeek-V4-Pro
- 43GPT-6 Sol vs. GPT-5.6 Luna
- 44Claude Opus 5 vs. GPT-6 Sol
- 45Claude Sonnet 5.5 vs. GLM-5.3-Flash
- 46GLM-5.3-Flash vs. Qwen 3.8 27B
- 47Claude Fable 5.1 vs. GLM-5.3-Flash
- 48DeepSeek-V4-Pro vs. GLM-5.3-Flash
- 49GPT-6 Sol vs. Mistral Large 4
- 50GPT-6 Sol vs. Gemini 4 Argon
- 51GPT-6 Sol vs. Gemini 3.6 Flash
- 52GLM-5.3-Flash vs. Qwen 3.8 Max 0902
- 53Claude Opus 4.6 vs. GPT-6 Sol
- 54GLM-5.3-Flash vs. MiMo-V2.5-Pro
- 55GLM-5.3-Flash vs. GLM-5.2
- 56GPT-6 Sol vs. Muse Wonder
- 57GPT-5.6 Luna vs. GLM-5.3-Flash
- 58Claude Haiku 4.5 vs. GPT-6 Sol
- 59GPT-6 Sol vs. GPT-5.5
- 60GPT-6.1 Terra vs. GPT-6 Sol
- 61GPT-5.5 vs. GLM-5.3-Flash
- 62Grok 4.3 vs. GLM-5.3-Flash
- 63Kimi K3.1 Pro vs. GLM-5.3-Flash
- 64GPT-6.1 Terra vs. GLM-5.3-Flash
- 65GPT-6 Sol vs. Gemini 4 Carbon
- 66Gemini 4 Argon vs. GLM-5.3-Flash