Model vs model
DeepSeek V4 Pro vs GLM 5.3
DeepSeek V4 Pro and GLM 5.3 are both in llmwise. What each gets on every plan, what it reads, how it's served and what happens when its provider fails, from the catalog and the code that runs them.
Model prices and specs checked against OpenRouter's DeepSeek V4 Pro page, OpenRouter's GLM 5.3 page. Updated .
Short answer
They cost the same in llmwise: up to 250 messages a month on Pro on either. Beyond that, they read the same files and neither is easier to try. In our test runs, DeepSeek V4 Pro passed 45 of the 50 prompts both answered and GLM 5.3 48; 5 prompts split them, most on coding (4 to 5).
DeepSeek V4 Pro vs GLM 5.3, prompt by prompt
Every prompt DeepSeek V4 Pro and GLM 5.3 both answered, compared directly, their biggest differences first. One run each, through OpenRouter: a wait depends on the provider and the load that day, so a lead under 10% counts as close.
Of the 50 prompts both answered, both passed 44, only DeepSeek V4 Pro passed 1, only GLM 5.3 passed 4, and neither passed 1. DeepSeek V4 Pro answered sooner on 2 of the 50 and GLM 5.3 on 44; the rest were within 10% of each other. The 50 replies cost $0.1030 on DeepSeek V4 Pro and $0.0364 on GLM 5.3: 2.8× less on GLM 5.3.
The 5 prompts only one of DeepSeek V4 Pro and GLM 5.3 passed
Parse CSV with quoted fields (coding): GLM 5.3 passed and DeepSeek V4 Pro didn't. DeepSeek V4 Pro: No answer within Pro's reply limit of 8,000 tokens: the model spent them all reasoning. GLM 5.3: All 8 tests passed.
A product announcement with five rules (writing): GLM 5.3 passed and DeepSeek V4 Pro didn't. DeepSeek V4 Pro: Graded 3.7 of 5 on average (lowest 2); but doesn't end with a question. GLM 5.3: Graded 4.3 of 5 on average (lowest 4).
An article in three bullets (summarization): DeepSeek V4 Pro passed and GLM 5.3 didn't. DeepSeek V4 Pro: Graded 4.3 of 5 on average (lowest 4). GLM 5.3: Graded 4.3 of 5 on average (lowest 3); but 68 words, over the 60 allowed.
An email thread in one sentence (summarization): GLM 5.3 passed and DeepSeek V4 Pro didn't. DeepSeek V4 Pro: Graded 4.7 of 5 on average (lowest 4); but 33 words, over the 30 allowed. GLM 5.3: Graded 4.3 of 5 on average (lowest 3).
A frustrated customer (customer support): GLM 5.3 passed and DeepSeek V4 Pro didn't. DeepSeek V4 Pro: Graded 3.3 of 5 on average (lowest 2). GLM 5.3: Graded 4.7 of 5 on average (lowest 4).
Job by job, the widest gaps first
Coding: DeepSeek V4 Pro passed 4 of 5 and GLM 5.3 5 of 5. GLM 5.3 answered 19.1× sooner at the median, 20.1 s against 1.1 s. GLM 5.3 cost 9.0× less, $0.0662 against $0.0073 for the 5 replies. Their replies ran to about the same length.
Customer support: DeepSeek V4 Pro passed 4 of 5 and GLM 5.3 5 of 5. GLM 5.3 answered 2.2× sooner at the median, 5.1 s against 2.3 s. GLM 5.3 cost 2.6× less, $0.0061 against $0.0023 for the 5 replies. GLM 5.3's replies ran 15% longer, in tokens of reply, thinking not counted.
Writing: DeepSeek V4 Pro passed 3 of 5 and GLM 5.3 4 of 5. GLM 5.3 answered 1.3× sooner at the median, 2.2 s against 1.8 s. DeepSeek V4 Pro cost 1.3× less, $0.0022 against $0.0029 for the 5 replies. Their replies ran to about the same length.
SQL: DeepSeek V4 Pro passed 5 of 5 and GLM 5.3 5 of 5. GLM 5.3 answered 3.2× sooner at the median, 3.8 s against 1.2 s. GLM 5.3 cost 3.1× less, $0.0049 against $0.0016 for the 5 replies. DeepSeek V4 Pro's replies ran 26% longer, in tokens of reply, thinking not counted.
Math: DeepSeek V4 Pro passed 5 of 5 and GLM 5.3 5 of 5. GLM 5.3 answered 2.9× sooner at the median, 2.7 s against 0.9 s. GLM 5.3 cost 1.9× less, $0.0033 against $0.0018 for the 5 replies. Their replies ran to about the same length.
Summarization: DeepSeek V4 Pro passed 4 of 5 and GLM 5.3 4 of 5. GLM 5.3 answered 2.8× sooner at the median, 3.1 s against 1.1 s. GLM 5.3 cost 1.7× less, $0.0045 against $0.0027 for the 5 replies. Their replies ran to about the same length.
Agents and tool use: DeepSeek V4 Pro passed 5 of 5 and GLM 5.3 5 of 5. GLM 5.3 answered 3.7× sooner at the median, 3.3 s against 0.9 s. DeepSeek V4 Pro cost 1.6× less, $0.0014 against $0.0022 for the 5 replies. DeepSeek V4 Pro's replies ran 12% longer, in tokens of reply, thinking not counted.
RAG and answering from documents: DeepSeek V4 Pro passed 5 of 5 and GLM 5.3 5 of 5. GLM 5.3 answered 3.0× sooner at the median, 1.9 s against 0.6 s. DeepSeek V4 Pro cost 1.5× less, $0.0017 against $0.0025 for the 5 replies. GLM 5.3's replies ran 19% longer, in tokens of reply, thinking not counted.
Translation: DeepSeek V4 Pro passed 5 of 5 and GLM 5.3 5 of 5. GLM 5.3 answered 2.7× sooner at the median, 4.3 s against 1.6 s. GLM 5.3 cost 1.3× less, $0.0045 against $0.0035 for the 5 replies. GLM 5.3's replies ran 47% longer, in tokens of reply, thinking not counted.
Data analysis: DeepSeek V4 Pro passed 5 of 5 and GLM 5.3 5 of 5. GLM 5.3 answered 1.3× sooner at the median, 2.5 s against 1.9 s. DeepSeek V4 Pro cost 1.2× less, $0.0081 against $0.0096 for the 5 replies. GLM 5.3's replies ran 31% longer, in tokens of reply, thinking not counted.
All 50 prompts: who passed, who answered sooner, who cost less
| Prompt | Result | Sooner | Cheaper |
|---|---|---|---|
| Turn a title into a URL slug | Both passed | GLM 5.3, 4.9×took 2.1 s and 0.4 s | GLM 5.3, 1.3×cost $0.0013 and $0.0010 |
| Parse a duration like “1h 30m” | Both passed | GLM 5.3, 19.1×took 20.1 s and 1.1 s | GLM 5.3, 2.1×cost $0.0030 and $0.0014 |
| Merge overlapping intervals | Both passed | GLM 5.3, 7.8×took 6.6 s and 0.8 s | DeepSeek V4 Pro, 1.7×cost $0.0005 and $0.0008 |
| Evaluate an arithmetic expression, no eval | Both passed | GLM 5.3, 3.2×took 40.3 s and 12.5 s | GLM 5.3, 17.1×cost $0.0291 and $0.0017 |
| Parse CSV with quoted fields | Only GLM 5.3 | GLM 5.3, 26.2×took 69.1 s and 2.6 s | GLM 5.3, 13.5×cost $0.0323 and $0.0024 |
| Announce a second bakery shop on LinkedIn | Both passed | DeepSeek V4 Pro, 1.5×took 1.9 s and 2.9 s | GLM 5.3, 2.2×cost $0.0008 and $0.0004 |
| Rewrite corporate jargon in plain words | Both passed | DeepSeek V4 Pro, 1.5×took 1.2 s and 1.8 s | GLM 5.3, 2.9×cost $0.0006 and $0.0002 |
| Decline a meeting and offer two times | Both passed | GLM 5.3, 1.6×took 2.2 s and 1.4 s | GLM 5.3, 1.2×cost $0.0003 and $0.0003 |
| A product announcement with five rules | Only GLM 5.3 | GLM 5.3, 4.5×took 3.8 s and 0.8 s | DeepSeek V4 Pro, 5.3×cost $0.0001 and $0.0008 |
| Argue both sides of free buses | Neither passed | GLM 5.3, 4.4×took 7.8 s and 1.8 s | DeepSeek V4 Pro, 4.0×cost $0.0003 and $0.0013 |
| A discount, then sales tax | Both passed | GLM 5.3, 2.9×took 2.7 s and 0.9 s | Closecost $0.0002 and $0.0002 |
| Pens at 3 for $4 | Both passed | GLM 5.3, 1.7×took 2.6 s and 1.5 s | GLM 5.3, 8.7×cost $0.0016 and $0.0002 |
| Compound interest over three years | Both passed | GLM 5.3, 2.6×took 1.5 s and 0.6 s | DeepSeek V4 Pro, 1.6×cost $0.0004 and $0.0005 |
| Four-digit numbers whose digits sum to 9 | Both passed | GLM 5.3, 1.7×took 3.2 s and 1.9 s | GLM 5.3, 2.4×cost $0.0006 and $0.0003 |
| The highest of three dice is a 5 | Both passed | GLM 5.3, 4.0×took 3.5 s and 0.9 s | Closecost $0.0006 and $0.0006 |
| An article in three bullets | Only DeepSeek V4 Pro | GLM 5.3, 2.2×took 6.1 s and 2.8 s | GLM 5.3, 4.6×cost $0.0021 and $0.0004 |
| An email thread in one sentence | Only GLM 5.3 | GLM 5.3, 2.7×took 2.8 s and 1.0 s | DeepSeek V4 Pro, 1.6×cost $0.0001 and $0.0002 |
| Decisions and action items from a meeting | Both passed | Closetook 1.5 s and 1.5 s | GLM 5.3, 2.1×cost $0.0005 and $0.0002 |
| A quarterly memo for the CEO | Both passed | GLM 5.3, 2.8×took 3.1 s and 1.1 s | DeepSeek V4 Pro, 5.6×cost $0.0002 and $0.0010 |
| A study with a negative result | Both passed | GLM 5.3, 4.2×took 3.5 s and 0.8 s | GLM 5.3, 2.0×cost $0.0016 and $0.0008 |
| The region with the most revenue | Both passed | Closetook 2.0 s and 2.1 s | GLM 5.3, 3.6×cost $0.0014 and $0.0004 |
| Average order value in August | Both passed | GLM 5.3, 1.9×took 3.7 s and 1.9 s | GLM 5.3, 5.6×cost $0.0021 and $0.0004 |
| Revenue change from July to August | Both passed | GLM 5.3, 1.8×took 2.5 s and 1.4 s | Closecost $0.0017 and $0.0016 |
| A median, filtered two ways | Both passed | GLM 5.3, 1.4×took 1.3 s and 1.0 s | DeepSeek V4 Pro, 1.3×cost $0.0008 and $0.0011 |
| Correlation between ad spend and sign-ups | Both passed | GLM 5.3, 7.4×took 41.2 s and 5.6 s | DeepSeek V4 Pro, 2.9×cost $0.0021 and $0.0062 |
| A late order | Both passed | GLM 5.3, 7.7×took 20.2 s and 2.6 s | GLM 5.3, 10.4×cost $0.0041 and $0.0004 |
| A return inside the window | Both passed | GLM 5.3, 1.5×took 2.4 s and 1.6 s | GLM 5.3, 4.0×cost $0.0009 and $0.0002 |
| A frustrated customer | Only GLM 5.3 | GLM 5.3, 3.7×took 8.6 s and 2.3 s | GLM 5.3, 1.6×cost $0.0005 and $0.0003 |
| A refund request outside the window | Both passed | GLM 5.3, 3.4×took 3.9 s and 1.1 s | DeepSeek V4 Pro, 3.4×cost $0.0003 and $0.0009 |
| A message with a planted instruction | Both passed | Closetook 5.1 s and 5.3 s | DeepSeek V4 Pro, 1.5×cost $0.0003 and $0.0005 |
| A delivery message into Spanish | Both passed | GLM 5.3, 2.9×took 4.3 s and 1.5 s | GLM 5.3, 4.0×cost $0.0009 and $0.0002 |
| A product description into French | Both passed | GLM 5.3, 2.1×took 3.1 s and 1.5 s | DeepSeek V4 Pro, 1.3×cost $0.0002 and $0.0003 |
| A meeting note into German | Both passed | GLM 5.3, 13.9×took 22.0 s and 1.6 s | GLM 5.3, 5.4×cost $0.0010 and $0.0002 |
| Idioms into natural Japanese | Both passed | GLM 5.3, 2.8×took 4.7 s and 1.7 s | GLM 5.3, 1.3×cost $0.0015 and $0.0012 |
| A lease clause into Brazilian Portuguese | Both passed | GLM 5.3, 2.2×took 3.7 s and 1.7 s | DeepSeek V4 Pro, 1.9×cost $0.0008 and $0.0016 |
| Customers in one country | Both passed | GLM 5.3, 2.4×took 1.9 s and 0.8 s | GLM 5.3, 1.3×cost $0.0002 and $0.0001 |
| Count orders by status | Both passed | GLM 5.3, 2.4×took 2.7 s and 1.2 s | GLM 5.3, 1.5×cost $0.0002 and $0.0001 |
| Revenue by category | Both passed | GLM 5.3, 3.0×took 3.8 s and 1.2 s | Closecost $0.0002 and $0.0002 |
| Every customer, even those without orders | Both passed | GLM 5.3, 4.6×took 4.5 s and 1.0 s | GLM 5.3, 3.9×cost $0.0028 and $0.0007 |
| Monthly revenue with a running total | Both passed | GLM 5.3, 10.7×took 34.4 s and 3.2 s | GLM 5.3, 4.0×cost $0.0016 and $0.0004 |
| A fact from one section | Both passed | GLM 5.3, 2.5×took 2.2 s and 0.9 s | DeepSeek V4 Pro, 1.1×cost $0.0002 and $0.0003 |
| Core hours and start times | Both passed | GLM 5.3, 5.0×took 2.5 s and 0.5 s | DeepSeek V4 Pro, 1.3×cost $0.0006 and $0.0007 |
| Two sections in one answer | Both passed | GLM 5.3, 2.5×took 1.3 s and 0.5 s | DeepSeek V4 Pro, 1.6×cost $0.0003 and $0.0005 |
| A later amendment changes the answer | Both passed | Closetook 1.3 s and 1.3 s | DeepSeek V4 Pro, 1.7×cost $0.0004 and $0.0006 |
| A question the handbook doesn't answer | Both passed | GLM 5.3, 3.0×took 1.9 s and 0.6 s | DeepSeek V4 Pro, 2.0×cost $0.0002 and $0.0005 |
| Pick the tool and work out the date | Both passed | GLM 5.3, 3.6×took 3.2 s and 0.9 s | Closecost $0.0002 and $0.0002 |
| Convert a currency | Both passed | GLM 5.3, 3.0×took 3.4 s and 1.1 s | DeepSeek V4 Pro, 1.3×cost $0.0001 and $0.0001 |
| Book a meeting from a sentence | Both passed | GLM 5.3, 2.1×took 3.5 s and 1.7 s | DeepSeek V4 Pro, 2.2×cost $0.0003 and $0.0006 |
| Search, but don't book | Both passed | GLM 5.3, 2.4×took 1.3 s and 0.5 s | GLM 5.3, 1.1×cost $0.0006 and $0.0005 |
| Two calls with a unit conversion | Both passed | GLM 5.3, 4.8×took 3.3 s and 0.7 s | DeepSeek V4 Pro, 4.1×cost $0.0002 and $0.0008 |
DeepSeek V4 Pro vs GLM 5.3 in our test runs
DeepSeek V4 Pro and GLM 5.3 on the same prompts, job by job: how many replies passed their check.
Based on 100 of our test runs on , through OpenRouter with the app's own prompt and settings. Updated .
| Job | DeepSeek V4 Pro | GLM 5.3 |
|---|---|---|
| Coding | 4 of 5 | 5 of 5 |
| Writing | 3 of 5 | 4 of 5 |
| Math | 5 of 5 | 5 of 5 |
| Summarization | 4 of 5 | 4 of 5 |
| Data analysis | 5 of 5 | 5 of 5 |
| Customer support | 4 of 5 | 5 of 5 |
| Translation | 5 of 5 | 5 of 5 |
| SQL | 5 of 5 | 5 of 5 |
| RAG and answering from documents | 5 of 5 | 5 of 5 |
| Agents and tool use | 5 of 5 | 5 of 5 |
| All jobs | 45 of 50 · 1 message each · $0.0021 a reply | 48 of 50 · 1 message each · $0.0007 a reply |
The same prompts, sent to both through llmwise's own pipeline and checked the same way: five for each job. A bold count is the one that passed more. Messages: what each reply counted as on Pro. Cost: what OpenRouter charged us per reply, on average. Every prompt, and how it's scored.
Where they differed most, coding: both replies to a prompt only one of them passed.
A hard prompt: “Parse CSV with quoted fields”, in full.
DeepSeek V4 Pro
Failed: No answer within Pro's reply limit of 8,000 tokens: the model spent them all reasoning.
(no reply)
493 tokens in, 8,000 out (7,805 of them reasoning) · 69.1 s · $0.0323 · 1 message on Pro · answered by deepseek/deepseek-v4-pro-0813 via CoreWeave ·
GLM 5.3
Passed: All 8 tests passed.
```javascript function parseCsv(text) { if (text === '') return []; const rows = []; let row = []; let field = ''; let inQuotes = false; let i = 0; const n = text.length; while (i < n) { const c = text[i]; if (inQuotes) { if (c === '"') { if (text[i + 1] === '"') { field += '"'; i += 2; } else { inQuotes = false; i++; } } else { field += c; i++; } continue; } if (c === '"' && field === '' && (i === 0 || /[\n\r,]/.test(text[i - 1]))) { inQuotes = true; i++; } else if (c === ',') { row.push(field); field = ''; i++; } else if (c === '\r' && text[i + 1] === '\n') { row.push(field); rows.push(row); row = []; field = ''; i += 2; } else if (c === '\n' || c === '\r') { row.push(field); rows.push(row); row = []; field = ''; i++; } else { field += c; i++; } } // Only emit a final row if there's a pending field/row (avoids trailing newline creating empty row) if (field !== '' || row.length > 0) { row.push(field); rows.push(row); } return rows; } ``` Notes on behavior: - A quote only starts a quoted field at the beginning of a field (start of input, after a comma, or after a line break), per your third rule; otherwise `"` is literal. - `""` inside quotes becomes a single `"`. - Embedded `\n`/`\r\n` inside quotes stays in the field; a trailing newline at the end of input doesn't create an empty final row; `''` returns `[]`.518 tokens in, 463 out (7 of them reasoning) · 2.6 s · $0.0024 · 1 message on Pro · answered by z-ai/glm-5.3 via Wafer ·
DeepSeek V4 Pro and GLM 5.3 on every plan
Whether the one-time free trial reaches each model, then each paid plan's messages on it.
| Plan | Price | DeepSeek V4 Pro | GLM 5.3 |
|---|---|---|---|
| Free | $0 | In the one-time trial of 5 messages | In the one-time trial of 5 messages |
| Pro | $20 a month | Up to 250 a month | Up to 250 a month |
| Max | $50 a month | Up to 800 a month | Up to 800 a month |
| Ultra | $100 a month | Up to 1,800 a month | Up to 1,800 a month |
| Studio | $200 a month | Up to 4,000 a month | Up to 4,000 a month |
Prices don't include tax, which is added where it applies and shown before you pay. A paid plan's month is one allowance shared by every model, so each monthly count is the most you get if all of it goes to that model. It renews each billing period; everyday models refill daily at 00:00 UTC. Long chats count more per reply. How pricing works.
Every limit is published. Paid plans also have a monthly fair-use limit on AI cost: Pro $7.50, Max $20, Ultra $42, Studio $85. Using every message on your plan at typical sizes stays under it; very large messages and heavy research use it faster. Every limit, explained.
What differs
Messages on Pro
They cost the same in llmwise: up to 250 messages a month on Pro on either.
Context window
Both take up to 1.05M tokens of context. A chat in llmwise holds up to 200k tokens, which fits in either, so the difference shows only through each maker's own API.
Images and PDFs
DeepSeek V4 Pro and GLM 5.3 don't read images. DeepSeek V4 Pro and GLM 5.3 get a PDF's text rather than the file itself.
On Free
Both are in the free trial.
Where messages go
DeepSeek V4 Pro: Served through OpenRouter, only by hosts that don't store or train on prompts. The maker's own endpoint is never asked. GLM 5.3: Served through OpenRouter, only by hosts that don't store or train on prompts. The maker's own endpoint is never asked.
Fact by fact
| Fact | DeepSeek V4 Pro | GLM 5.3 |
|---|---|---|
| Context window | 1.05M tokens | 1.05M tokens |
| Reads images | No | No |
| PDFs | Text only | Text only |
| Reasoning | Yes | Yes |
| API price (September 2026) | $0.44 in / $2.90 out per million tokens | $1.40 in / $4.40 out per million tokens |
| A typical message at API prices (4,000 tokens in, 700 out) | $0.0038 | $0.0087 |
| A $10 top-up adds | 200 messages | 200 messages |
| Where a message goes | Served through OpenRouter, only by hosts that don't store or train on prompts. The maker's own endpoint is never asked. | Served through OpenRouter, only by hosts that don't store or train on prompts. The maker's own endpoint is never asked. |
| If the provider fails | When one host is down, OpenRouter moves the request to another host that meets the same rules. | When one host is down, OpenRouter moves the request to another host that meets the same rules. |
| Anthropic's safety fallback | Doesn't apply | Doesn't apply |
DeepSeek V4 Pro or GLM 5.3?
From the facts above and our test runs: the rest is how their answers suit your work, which one chat can show you.
Pick DeepSeek V4 Pro: it costs its maker less to run ($0.0038 a typical message at API prices), though in llmwise the count is the same.
Each model's page, the families, and other pairs
DeepSeek V4 Pro vs GLM 5.3 is one pair of models. The page below covers the whole families.
- DeepSeek V4 Pro: price, limits and messages on every plan
- GLM 5.3: price, limits and messages on every plan
- DeepSeek vs GLM
- Claude Opus 5.5 vs DeepSeek V4 Pro
- DeepSeek V4 Pro vs Kimi K3
- Claude Sonnet 5 vs DeepSeek V4 Pro
- GLM 5.3 vs GLM 5.3 Flash
- Kimi K3 vs GLM 5.3
- Claude Sonnet 5 vs GLM 5.3
- Every model-vs-model page
DeepSeek V4 Pro is a DeepSeek model; GLM 5.3 is a GLM model.
Questions
Is DeepSeek V4 Pro or GLM 5.3 cheaper in llmwise?
They cost the same in llmwise: up to 250 messages a month on Pro on either. Every paid plan's monthly allowance is shared by all models, so each count is the most you get if it all goes to that model.
Can I try DeepSeek V4 Pro and GLM 5.3 for free?
Yes: both are in the free trial of 5 messages.
Which has the bigger context window, DeepSeek V4 Pro or GLM 5.3?
Neither: both take 1.05M tokens. A chat in llmwise holds up to 200k tokens, which fits in either, so the difference shows only through each maker's own API.
Can I use DeepSeek V4 Pro and GLM 5.3 in the same chat?
Yes. Pick DeepSeek V4 Pro for one message and GLM 5.3 for the next; the second sees the whole chat, including the first one's answer.
Which did better in your test runs, DeepSeek V4 Pro or GLM 5.3?
On the same 50 prompts, run on September 27, 2026, DeepSeek V4 Pro passed 45 and GLM 5.3 passed 48. The table on this page has each job, and every reply is published.
Claude, GPT, Gemini, DeepSeek, Grok, Kimi, and GLM, in one chat.
See what a message costs before you send it. Free is 5 messages to try; sign in with an email link, no password or card.