Model vs model

Claude Haiku 4.5 vs GLM 5.3

Claude Haiku 4.5 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.

Start free See pricing

Model prices and specs checked September 25, 2026 against OpenRouter's Claude Haiku 4.5 page, OpenRouter's GLM 5.3 page. Updated September 28, 2026.

Short answer

They cost the same in llmwise: up to 250 messages a month on Pro on either. Otherwise, only Claude Haiku 4.5 reads images and only Claude Haiku 4.5 reads a PDF as the whole file. In our test runs, Claude Haiku 4.5 passed 43 of the 50 prompts both answered and GLM 5.3 48; 9 prompts split them, most on coding (3 to 5).

Claude Haiku 4.5 vs GLM 5.3, prompt by prompt

Every prompt Claude Haiku 4.5 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 41, only Claude Haiku 4.5 passed 2, only GLM 5.3 passed 7, and neither passed 0. Claude Haiku 4.5 answered sooner on 10 of the 50 and GLM 5.3 on 35; the rest were within 10% of each other. The 50 replies cost $0.0741 on Claude Haiku 4.5 and $0.0364 on GLM 5.3: 2.0× less on GLM 5.3.

The 9 prompts only one of Claude Haiku 4.5 and GLM 5.3 passed

Evaluate an arithmetic expression, no eval (coding): GLM 5.3 passed and Claude Haiku 4.5 didn't. Claude Haiku 4.5: 14 of 15 tests passed. First failure: evaluate("-2 ^ 2"): Expected values to be strictly deep-equal: GLM 5.3: All 15 tests passed.
Parse CSV with quoted fields (coding): GLM 5.3 passed and Claude Haiku 4.5 didn't. Claude Haiku 4.5: 5 of 8 tests passed. First failure: parseCsv('"line1\nline2",end\r\nnext,row\r\n'): Expected values to be strictly deep-equal: GLM 5.3: All 8 tests passed.
A product announcement with five rules (writing): GLM 5.3 passed and Claude Haiku 4.5 didn't. Claude Haiku 4.5: Graded 3.7 of 5 on average (lowest 3). GLM 5.3: Graded 4.3 of 5 on average (lowest 4).
Argue both sides of free buses (writing): Claude Haiku 4.5 passed and GLM 5.3 didn't. Claude Haiku 4.5: Graded 4.0 of 5 on average (lowest 4). GLM 5.3: Graded 3.7 of 5 on average (lowest 3); but a paragraph of 92 words, over the 90 allowed.
An article in three bullets (summarization): Claude Haiku 4.5 passed and GLM 5.3 didn't. Claude Haiku 4.5: Graded 4.0 of 5 on average (lowest 3). GLM 5.3: Graded 4.3 of 5 on average (lowest 3); but 68 words, over the 60 allowed.
Average order value in August (data analysis): GLM 5.3 passed and Claude Haiku 4.5 didn't. Claude Haiku 4.5: Final answer 275.00; expected 300. GLM 5.3: Final answer 300.00: right.
Correlation between ad spend and sign-ups (data analysis): GLM 5.3 passed and Claude Haiku 4.5 didn't. Claude Haiku 4.5: Final answer 0.99; expected 0.97. GLM 5.3: Final answer 0.97: right.
A frustrated customer (customer support): GLM 5.3 passed and Claude Haiku 4.5 didn't. Claude Haiku 4.5: Graded 3.3 of 5 on average (lowest 3). GLM 5.3: Graded 4.7 of 5 on average (lowest 4).
A message with a planted instruction (customer support): GLM 5.3 passed and Claude Haiku 4.5 didn't. Claude Haiku 4.5: Graded 4.3 of 5 on average (lowest 3); but 165 words, over the 150 allowed. GLM 5.3: Graded 4.3 of 5 on average (lowest 4).

Job by job, the widest gaps first

Customer support: Claude Haiku 4.5 passed 3 of 5 and GLM 5.3 5 of 5. GLM 5.3 answered 1.2× sooner at the median, 2.7 s against 2.3 s. GLM 5.3 cost 3.1× less, $0.0073 against $0.0023 for the 5 replies. Claude Haiku 4.5's replies ran 32% longer, in tokens of reply, thinking not counted.
Coding: Claude Haiku 4.5 passed 3 of 5 and GLM 5.3 5 of 5. GLM 5.3 answered 2.2× sooner at the median, 2.3 s against 1.1 s. GLM 5.3 cost 1.9× less, $0.0137 against $0.0073 for the 5 replies. Claude Haiku 4.5's replies ran 70% longer, in tokens of reply, thinking not counted.
Data analysis: Claude Haiku 4.5 passed 3 of 5 and GLM 5.3 5 of 5. GLM 5.3 answered 1.4× sooner at the median, 2.7 s against 1.9 s. GLM 5.3 cost 1.3× less, $0.0125 against $0.0096 for the 5 replies. Claude Haiku 4.5's replies ran 154% longer, in tokens of reply, thinking not counted.
Summarization: Claude Haiku 4.5 passed 5 of 5 and GLM 5.3 4 of 5. GLM 5.3 answered 1.5× sooner at the median, 1.7 s against 1.1 s. GLM 5.3 cost 1.9× less, $0.0051 against $0.0027 for the 5 replies. Their replies ran to about the same length.
Math: Claude Haiku 4.5 passed 5 of 5 and GLM 5.3 5 of 5. GLM 5.3 answered 2.4× sooner at the median, 2.2 s against 0.9 s. GLM 5.3 cost 4.4× less, $0.0077 against $0.0018 for the 5 replies. Claude Haiku 4.5's replies ran 189% longer, in tokens of reply, thinking not counted.
SQL: Claude Haiku 4.5 passed 5 of 5 and GLM 5.3 5 of 5. Their median waits were close, 1.2 s against 1.2 s. GLM 5.3 cost 3.1× less, $0.0049 against $0.0016 for the 5 replies. Claude Haiku 4.5's replies ran 29% longer, in tokens of reply, thinking not counted.
Agents and tool use: Claude Haiku 4.5 passed 5 of 5 and GLM 5.3 5 of 5. GLM 5.3 answered 1.3× sooner at the median, 1.1 s against 0.9 s. GLM 5.3 cost 2.1× less, $0.0047 against $0.0022 for the 5 replies. Claude Haiku 4.5's replies ran 87% longer, in tokens of reply, thinking not counted.
Translation: Claude Haiku 4.5 passed 5 of 5 and GLM 5.3 5 of 5. GLM 5.3 answered 1.2× sooner at the median, 1.8 s against 1.6 s. GLM 5.3 cost 2.1× less, $0.0074 against $0.0035 for the 5 replies. Claude Haiku 4.5's replies ran 28% longer, in tokens of reply, thinking not counted.
RAG and answering from documents: Claude Haiku 4.5 passed 5 of 5 and GLM 5.3 5 of 5. GLM 5.3 answered 1.9× sooner at the median, 1.2 s against 0.6 s. GLM 5.3 cost 2.0× less, $0.0050 against $0.0025 for the 5 replies. Claude Haiku 4.5's replies ran 114% longer, in tokens of reply, thinking not counted.
Writing: Claude Haiku 4.5 passed 4 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. GLM 5.3 cost 2.0× less, $0.0057 against $0.0029 for the 5 replies. Their replies ran to about the same length.

All 50 prompts: who passed, who answered sooner, who cost less

Claude Haiku 4.5 and GLM 5.3 on each prompt of our test runs
Prompt	Result	Sooner	Cheaper
Turn a title into a URL slug	Both passed	GLM 5.3, 3.5×took 1.5 s and 0.4 s	Closecost $0.0010 and $0.0010
Parse a duration like “1h 30m”	Both passed	GLM 5.3, 2.2×took 2.3 s and 1.1 s	GLM 5.3, 1.5×cost $0.0022 and $0.0014
Merge overlapping intervals	Both passed	GLM 5.3, 2.3×took 2.0 s and 0.8 s	GLM 5.3, 2.1×cost $0.0017 and $0.0008
Evaluate an arithmetic expression, no eval	Only GLM 5.3	Claude Haiku 4.5, 1.7×took 7.6 s and 12.5 s	GLM 5.3, 3.3×cost $0.0056 and $0.0017
Parse CSV with quoted fields	Only GLM 5.3	GLM 5.3, 1.3×took 3.5 s and 2.6 s	GLM 5.3, 1.4×cost $0.0033 and $0.0024
Announce a second bakery shop on LinkedIn	Both passed	Claude Haiku 4.5, 1.1×took 2.6 s and 2.9 s	GLM 5.3, 3.4×cost $0.0013 and $0.0004
Rewrite corporate jargon in plain words	Both passed	Closetook 1.6 s and 1.8 s	GLM 5.3, 4.1×cost $0.0008 and $0.0002
Decline a meeting and offer two times	Both passed	GLM 5.3, 1.4×took 2.0 s and 1.4 s	GLM 5.3, 3.7×cost $0.0010 and $0.0003
A product announcement with five rules	Only GLM 5.3	GLM 5.3, 2.6×took 2.2 s and 0.8 s	GLM 5.3, 1.6×cost $0.0012 and $0.0008
Argue both sides of free buses	Only Claude Haiku 4.5	GLM 5.3, 2.0×took 3.4 s and 1.8 s	GLM 5.3, 1.1×cost $0.0014 and $0.0013
A discount, then sales tax	Both passed	GLM 5.3, 1.2×took 1.1 s and 0.9 s	GLM 5.3, 3.7×cost $0.0007 and $0.0002
Pens at 3 for $4	Both passed	GLM 5.3, 1.5×took 2.2 s and 1.5 s	GLM 5.3, 8.1×cost $0.0014 and $0.0002
Compound interest over three years	Both passed	GLM 5.3, 6.0×took 3.5 s and 0.6 s	GLM 5.3, 2.4×cost $0.0013 and $0.0005
Four-digit numbers whose digits sum to 9	Both passed	GLM 5.3, 1.5×took 2.9 s and 1.9 s	GLM 5.3, 9.6×cost $0.0024 and $0.0003
The highest of three dice is a 5	Both passed	GLM 5.3, 2.6×took 2.2 s and 0.9 s	GLM 5.3, 3.1×cost $0.0018 and $0.0006
An article in three bullets	Only Claude Haiku 4.5	Claude Haiku 4.5, 1.5×took 1.8 s and 2.8 s	GLM 5.3, 2.4×cost $0.0011 and $0.0004
An email thread in one sentence	Both passed	GLM 5.3, 1.3×took 1.3 s and 1.0 s	GLM 5.3, 3.1×cost $0.0007 and $0.0002
Decisions and action items from a meeting	Both passed	GLM 5.3, 1.1×took 1.7 s and 1.5 s	GLM 5.3, 4.5×cost $0.0011 and $0.0002
A quarterly memo for the CEO	Both passed	GLM 5.3, 1.4×took 1.5 s and 1.1 s	GLM 5.3, 1.2×cost $0.0012 and $0.0010
A study with a negative result	Both passed	GLM 5.3, 4.1×took 3.4 s and 0.8 s	GLM 5.3, 1.2×cost $0.0010 and $0.0008
The region with the most revenue	Both passed	GLM 5.3, 1.3×took 2.7 s and 2.1 s	GLM 5.3, 6.7×cost $0.0026 and $0.0004
Average order value in August	Only GLM 5.3	Closetook 2.1 s and 1.9 s	GLM 5.3, 6.3×cost $0.0023 and $0.0004
Revenue change from July to August	Both passed	GLM 5.3, 3.1×took 4.2 s and 1.4 s	GLM 5.3, 1.4×cost $0.0022 and $0.0016
A median, filtered two ways	Both passed	GLM 5.3, 2.1×took 2.0 s and 1.0 s	GLM 5.3, 1.5×cost $0.0016 and $0.0011
Correlation between ad spend and sign-ups	Only GLM 5.3	Claude Haiku 4.5, 1.1×took 5.0 s and 5.6 s	Claude Haiku 4.5, 1.7×cost $0.0037 and $0.0062
A late order	Both passed	Claude Haiku 4.5, 1.3×took 2.0 s and 2.6 s	GLM 5.3, 3.5×cost $0.0014 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, 5.7×cost $0.0013 and $0.0002
A frustrated customer	Only GLM 5.3	GLM 5.3, 1.3×took 3.0 s and 2.3 s	GLM 5.3, 5.0×cost $0.0016 and $0.0003
A refund request outside the window	Both passed	GLM 5.3, 2.4×took 2.7 s and 1.1 s	GLM 5.3, 1.4×cost $0.0013 and $0.0009
A message with a planted instruction	Only GLM 5.3	Claude Haiku 4.5, 1.7×took 3.2 s and 5.3 s	GLM 5.3, 3.8×cost $0.0018 and $0.0005
A delivery message into Spanish	Both passed	Closetook 1.5 s and 1.5 s	GLM 5.3, 5.0×cost $0.0011 and $0.0002
A product description into French	Both passed	Closetook 1.4 s and 1.5 s	GLM 5.3, 3.9×cost $0.0011 and $0.0003
A meeting note into German	Both passed	GLM 5.3, 1.2×took 1.8 s and 1.6 s	GLM 5.3, 5.6×cost $0.0010 and $0.0002
Idioms into natural Japanese	Both passed	GLM 5.3, 1.9×took 3.3 s and 1.7 s	GLM 5.3, 1.6×cost $0.0019 and $0.0012
A lease clause into Brazilian Portuguese	Both passed	GLM 5.3, 2.1×took 3.5 s and 1.7 s	GLM 5.3, 1.3×cost $0.0022 and $0.0016
Customers in one country	Both passed	GLM 5.3, 1.4×took 1.1 s and 0.8 s	GLM 5.3, 4.9×cost $0.0007 and $0.0001
Count orders by status	Both passed	Claude Haiku 4.5, 1.4×took 0.8 s and 1.2 s	GLM 5.3, 4.9×cost $0.0006 and $0.0001
Revenue by category	Both passed	Closetook 1.2 s and 1.2 s	GLM 5.3, 5.1×cost $0.0011 and $0.0002
Every customer, even those without orders	Both passed	GLM 5.3, 2.2×took 2.1 s and 1.0 s	GLM 5.3, 1.4×cost $0.0010 and $0.0007
Monthly revenue with a running total	Both passed	Claude Haiku 4.5, 2.0×took 1.6 s and 3.2 s	GLM 5.3, 4.1×cost $0.0016 and $0.0004
A fact from one section	Both passed	GLM 5.3, 1.2×took 1.1 s and 0.9 s	GLM 5.3, 3.5×cost $0.0009 and $0.0003
Core hours and start times	Both passed	GLM 5.3, 2.3×took 1.1 s and 0.5 s	GLM 5.3, 1.3×cost $0.0009 and $0.0007
Two sections in one answer	Both passed	GLM 5.3, 2.6×took 1.3 s and 0.5 s	GLM 5.3, 2.3×cost $0.0011 and $0.0005
A later amendment changes the answer	Both passed	GLM 5.3, 1.5×took 1.9 s and 1.3 s	GLM 5.3, 2.1×cost $0.0012 and $0.0006
A question the handbook doesn't answer	Both passed	GLM 5.3, 1.9×took 1.2 s and 0.6 s	GLM 5.3, 2.0×cost $0.0009 and $0.0005
Pick the tool and work out the date	Both passed	GLM 5.3, 1.2×took 1.1 s and 0.9 s	GLM 5.3, 3.8×cost $0.0008 and $0.0002
Convert a currency	Both passed	Claude Haiku 4.5, 1.1×took 1.0 s and 1.1 s	GLM 5.3, 6.1×cost $0.0008 and $0.0001
Book a meeting from a sentence	Both passed	Claude Haiku 4.5, 1.4×took 1.2 s and 1.7 s	GLM 5.3, 1.9×cost $0.0010 and $0.0006
Search, but don't book	Both passed	GLM 5.3, 2.1×took 1.1 s and 0.5 s	GLM 5.3, 1.8×cost $0.0010 and $0.0005
Two calls with a unit conversion	Both passed	GLM 5.3, 1.7×took 1.2 s and 0.7 s	GLM 5.3, 1.4×cost $0.0011 and $0.0008

Claude Haiku 4.5 vs GLM 5.3 in our test runs

Claude Haiku 4.5 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 September 27, 2026, through OpenRouter with the app's own prompt and settings. Updated September 28, 2026.

Claude Haiku 4.5 and GLM 5.3 in our test runs, job by job
Job	Claude Haiku 4.5	GLM 5.3
Coding	3 of 5	5 of 5
Writing	4 of 5	4 of 5
Math	5 of 5	5 of 5
Summarization	5 of 5	4 of 5
Data analysis	3 of 5	5 of 5
Customer support	3 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	43 of 50 · 1 message each · $0.0015 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: “Evaluate an arithmetic expression, no eval”, in full.

Claude Haiku 4.5

Failed: 14 of 15 tests passed. First failure: evaluate("-2 ^ 2"): Expected values to be strictly deep-equal:

```javascript
function evaluate(expression) {
  const tokens = tokenize(expression);
  const parser = new Parser(tokens);
  const result = parser.parseExpression();
  
  if (parser.pos !== tokens.length) {
    throw new Error("Unexpected tokens after expression");
  }
  
  return result;
}

function tokenize(expression) {
  const tokens = [];
  let i = 0;
  
  while (i < expression.length) {
    const ch = expression[i];
    
    if (/\s/.test(ch)) {
      i++;
      continue;
    }
    
    if (/\d/.test(ch)) {
      let num = '';
      while (i < expression.length && /[\d.]/.test(expression[i])) {
        num += expression[i];
        i++;
      }
      const parsed = parseFloat(num);
      if (isNaN(parsed)) {
        throw new Error(`Invalid number: ${num}`);
      }
      tokens.push({ type: 'NUMBER', value: parsed });
      continue;
    }
    
    if ('+-*/^()'.includes(ch)) {
      tokens.push({ type: ch, value: ch });
      i++;
      continue;
    }
    
    throw new Error(`Unexpected character: ${ch}`);
  }
  
  return tokens;
}

class Parser {
  constructor(tokens) {
    this.tokens = tokens;
    this.pos = 0;
  }
  
  peek() {
    return this.tokens[this.pos];
  }
  
  consume() {
    return this.tokens[this.pos++];
  }
  
  parseExpression() {
    return this.parseAddSub();
  }
  
  parseAddSub() {
    let left = this.parseMulDiv();
    
    while (this.peek() && (this.peek().type === '+' || this.peek().type === '-')) {
      const op = this.consume().type;
      const right = this.parseMulDiv();
      left = op === '+' ? left + right : left - right;
    }
    
    return left;
  }
  
  parseMulDiv() {
    let left = this.parsePower();
    
    while (this.peek() && (this.peek().type === '*' || this.peek().type === '/')) {
      const op = this.consume().type;
      const right = this.parsePower();
      left = op === '*' ? left * right : left / right;
    }
    
    return left;
  }
  
  parsePower() {
    let left = this.parseUnary();
    
    if (this.peek() && this.peek().type === '^') {
      this.consume();
      const right = this.parsePower();
      left = Math.pow(left, right);
    }
    
    return left;
  }
  
  parseUnary() {
    if (this.peek() && this.peek().type === '-') {
      this.consume();
      return -this.parseUnary();
    }
    
    if (this.peek() && this.peek().type === '+') {
      this.consume();
      return this.parseUnary();
    }
    
    return this.parsePrimary();
  }
  
  parsePrimary() {
    const token = this.peek();
    
    if (!token) {
      throw new Error("Unexpected end of expression");
    }
    
    if (token.type === 'NUMBER') {
      this.consume();
      return token.value;
    }
    
    if (token.type === '(') {
      this.consume();
      const result = this.parseExpression();
      
      if (!this.peek() || this.peek().type !== ')') {
        throw new Error("Missing closing parenthesis");
      }
      
      this.consume();
      return result;
    }
    
    throw new Error(`Unexpected token: ${token.value}`);
  }
}
```

599 tokens in, 1,007 out · 7.6 s · $0.0056 · 1 message on Pro · answered by anthropic/claude-haiku-4.5 via Amazon Bedrock · September 27, 2026

GLM 5.3

Passed: All 15 tests passed.

```javascript
function evaluate(expression) {
  if (typeof expression !== 'string') throw new Error('Invalid expression');
  const src = expression;
  let pos = 0;

  function skipSpaces() {
    while (pos < src.length && /\s/.test(src[pos])) pos++;
  }

  function parseExpr() {
    let left = parseTerm();
    for (;;) {
      skipSpaces();
      if (src[pos] === '+') { pos++; left += parseTerm(); }
      else if (src[pos] === '-') { pos++; left -= parseTerm(); }
      else return left;
    }
  }

  function parseTerm() {
    let left = parseUnary();
    for (;;) {
      skipSpaces();
      if (src[pos] === '*') { pos++; left *= parseUnary(); }
      else if (src[pos] === '/') { pos++; left /= parseUnary(); }
      else return left;
    }
  }

  function parseUnary() {
    skipSpaces();
    if (src[pos] === '-') { pos++; return -parseUnary(); }
    return parsePower();
  }

  function parsePower() {
    const base = parsePrimary();
    skipSpaces();
    if (src[pos] === '^') {
      pos++;
      return Math.pow(base, parseUnary()); // right-assoc, exponent may be unary
    }
    return base;
  }

  function parsePrimary() {
    skipSpaces();
    if (src[pos] === '(') {
      pos++;
      const value = parseExpr();
      skipSpaces();
      if (src[pos] !== ')') throw new Error('Invalid expression: expected )');
      pos++;
      return value;
    }
    if (src[pos] === '-') return parseUnary(); // handled here too for safety
    const start = pos;
    while (pos < src.length && /[0-9.]/.test(src[pos])) pos++;
    if (pos === start) throw new Error('Invalid expression: expected number');
    const text = src.slice(start, pos);
    if (!/^\d+(\.\d+)?$|^\.\d+$/.test(text)) throw new Error('Invalid number: ' + text);
    return parseFloat(text);
  }

  const result = parseExpr();
  skipSpaces();
  if (pos !== src.length) throw new Error('Invalid expression: unexpected trailing input');
  return result;
}
```

562 tokens in, 594 out (85 of them reasoning) · 12.5 s · $0.0017 · 1 message on Pro · answered by z-ai/glm-5.3 via Reka · September 27, 2026

Claude Haiku 4.5 and GLM 5.3 on every plan

Whether the one-time free trial reaches each model, then each paid plan's messages on it.

Messages on Claude Haiku 4.5 and GLM 5.3, plan by plan
Plan	Price	Claude Haiku 4.5	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
Claude Haiku 4.5 takes up to 200K tokens; GLM 5.3 up to 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.
Images and PDFs
GLM 5.3 doesn't read images. GLM 5.3 gets a PDF's text rather than the file itself.
On Free
Both are in the free trial.
Where messages go
Claude Haiku 4.5: Sent to Anthropic directly. 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

Claude Haiku 4.5 and GLM 5.3, fact by fact
Fact	Claude Haiku 4.5	GLM 5.3
Context window	200K tokens	1.05M tokens
Reads images	Yes	No
PDFs	Whole file	Text only
Reasoning	No	Yes
API price (September 2026)	$1.00 in / $5.00 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)	$0.0075	$0.0087
A $10 top-up adds	200 messages	200 messages
Where a message goes	Sent to Anthropic directly.	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	If Anthropic fails before the reply starts (an overload, a server error, a dropped connection), llmwise sends the same request to Claude Haiku 4.5 through OpenRouter instead.	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

API prices are what our model catalog lists (Claude: Anthropic's list price; GLM: Z.ai's list price). In llmwise you pay per message, not per token: the counts above are what you get.

Claude Haiku 4.5 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 Claude Haiku 4.5: it reads images; it reads a PDF as the whole file, charts and scans included; it costs its maker less to run ($0.0075 a typical message at API prices), though in llmwise the count is the same.

Each model's page, the families, and other pairs

Claude Haiku 4.5 vs GLM 5.3 is one pair of models. The page below covers the whole families.

Claude Haiku 4.5 is a Claude model; GLM 5.3 is a GLM model.

Questions

Is Claude Haiku 4.5 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 Claude Haiku 4.5 and GLM 5.3 for free?

Yes: both are in the free trial of 5 messages.

Which has the bigger context window, Claude Haiku 4.5 or GLM 5.3?

GLM 5.3: 1.05M tokens, against 200K 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 Claude Haiku 4.5 and GLM 5.3 in the same chat?

Yes. Pick Claude Haiku 4.5 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, Claude Haiku 4.5 or GLM 5.3?

On the same 50 prompts, run on September 27, 2026, Claude Haiku 4.5 passed 43 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.