ZMIME
Comparison · 3 models · Updated Oct 4, 2026

GLM-5 vs Claude Haiku 4.5 vs Qwen3 Max

Claude Haiku 4.5 comes out ahead, 58 to 55 and 50 on our weighted score, though GLM-5 is 22% cheaper per token.

  1. Z.ai (Zhipu)

    GLM-5

    Released Feb 12, 2026

    55/100
    • ECI145.8
    • Price$1.00 / $3.20
    • Context205K
  2. Our pick

    Anthropic

    Claude Haiku 4.5

    Released Oct 15, 2025

    58/100
    • ECI142.4
    • Price$1.00 / $5.00
    • Context200K
  3. Alibaba (Qwen)

    Qwen3 Max

    Released Sep 23, 2025

    50/100
    • ECI142.4
    • Price$1.20 / $6.00
    • Context262K
01 — Verdict

Claude Haiku 4.5 is our pick

Claude Haiku 4.5 is the better all-round choice, scoring 58/100 against GLM-5 (55) and Qwen3 Max (50). It leads on inputs & features. GLM-5 wins on capability and price. Qwen3 Max wins on context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityGLM-5Capabilities Index (ECI): GLM-5 145.8 · Claude Haiku 4.5 142.4 · Qwen3 Max 142.4
  • Lowest priceGLM-5GLM-5 $1.55 · Claude Haiku 4.5 $2.00 · Qwen3 Max $2.40 per 1M tokens (3:1 blend)
  • Longest contextQwen3 MaxQwen3 Max 262,144 · GLM-5 204,800 · Claude Haiku 4.5 200,000 tokens
  • Widest inputsClaude Haiku 4.5GLM-5: Text · Claude Haiku 4.5: Text, Images, PDFs · Qwen3 Max: Text
  • Self-hostingGLM-5Publishes downloadable weights
How the score is built
MeasureWeightGLM-5Claude Haiku 4.5Qwen3 Max
CapabilityCapabilities Index (ECI)50%736968
Price25%413632
Inputs & features15%358025
Context window10%323237
Overall100%55/10058/10050/100
02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

GLM-5 vs Claude Haiku 4.5 vs Qwen3 Max specifications side by side
SpecificationGLM-5Z.ai (Zhipu)Claude Haiku 4.5AnthropicQwen3 MaxAlibaba (Qwen)
Capability
Capabilities Index (ECI)145.8 (best)142.4142.4
ECI rank#74 of 148 (best)#90 of 148#91 of 148
GPQA DiamondGraduate-level science questions87.8% (best)71.2%72.6%
FrontierMath Tiers 1–3Research-level mathematics——19.0%
OTIS Mock AIME 2024–2025Competition mathematics80.0% (best)66.7%73.3%
SWE-bench VerifiedFixing real GitHub issues72.1%——
SimpleQA VerifiedShort factual questions—13.2%48.8% (best)
Price per million tokens
Input$1.00 (best)$1.00 (best)$1.20
Output$3.20 (best)$5.00$6.00
Cached input$0.20$0.10 (best)—
Blended (3:1)$1.55 (best)$2.00$2.40
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Z.AI APIOfficial Anthropic APIOfficial Alibaba API
Limits
Context window204,800 tokens200,000 tokens262,144 tokens (best)
Max output131,072 tokens (best)64,000 tokens65,536 tokens
Inputs and features
TextYesYesYes
ImagesNoYesNo
PDFsNoYesNo
AudioNoNoNo
VideoNoNoNo
ReasoningYesYesNo
Tool callingYesYesYes
Structured outputNoYesNo
Availability
WeightsOpenProprietaryProprietary
API model IDglm-5claude-haiku-4-5qwen3-max
API providers2734 (best)16
ReleasedFeb 12, 2026Oct 15, 2025Sep 23, 2025
Knowledge cutoff—Feb 28, 2025Apr 2025
03 — Cost

What would a month cost?

Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.

  • GLM-5$16.40
  • Claude Haiku 4.5$20.00
  • Qwen3 Max$24.00
04 — Questions

Which should you choose?

Which is better: GLM-5, Claude Haiku 4.5 or Qwen3 Max?

Claude Haiku 4.5 is the better all-round choice, scoring 58/100 against GLM-5 (55) and Qwen3 Max (50). It leads on inputs & features. GLM-5 wins on capability and price. Qwen3 Max wins on context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, GLM-5, Claude Haiku 4.5 or Qwen3 Max?

GLM-5 is cheaper at $1.00 input / $3.20 output per million tokens (official Z.AI API price). Claude Haiku 4.5 costs $1.00 input / $5.00 output per million tokens (official Anthropic API price); Qwen3 Max costs $1.20 input / $6.00 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $1.55 per million tokens for GLM-5 versus $2.00 for Claude Haiku 4.5 (1.3× as much) and $2.40 for Qwen3 Max (1.5× as much).

Which scores higher on benchmarks?

GLM-5 scores higher on the Capabilities Index (ECI): GLM-5 145.8 (#74 of 148), Claude Haiku 4.5 142.4 (#90 of 148) and Qwen3 Max 142.4 (#91 of 148). The confidence ranges of the top two overlap (143.9–147.7 vs 139.5–144.3), so treat the gap as small. On individual benchmarks: GPQA Diamond — GLM-5 87.8%, Qwen3 Max 72.6%, Claude Haiku 4.5 71.2%; OTIS Mock AIME 2024–2025 — GLM-5 80.0%, Qwen3 Max 73.3%, Claude Haiku 4.5 66.7%.

Which is better for coding?

There are no published SWE-bench Verified results for Claude Haiku 4.5 and Qwen3 Max yet, so there is no like-for-like coding score. On overall capability, GLM-5 leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.

Which has the bigger context window?

Qwen3 Max has the largest context window at 262,144 tokens, against 204,800 for GLM-5 and 200,000 for Claude Haiku 4.5. Maximum output per response: GLM-5 up to 131,072, Claude Haiku 4.5 up to 64,000, Qwen3 Max up to 65,536 tokens.

Which can read images, PDFs, audio or video?

GLM-5 accepts text; Claude Haiku 4.5 accepts text, images and PDFs; Qwen3 Max accepts text. Claude Haiku 4.5 handles the widest range of inputs.

Are any of these open source?

GLM-5 publishes its weights and can be self-hosted; Claude Haiku 4.5 and Qwen3 Max is proprietary.

Which is newer?

GLM-5 is the newest, released Feb 12, 2026. Claude Haiku 4.5 came out Oct 15, 2025; Qwen3 Max came out Sep 23, 2025. Knowledge cutoff: Claude Haiku 4.5 Feb 28, 2025, Qwen3 Max Apr 2025.

How do you decide the winner?

Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.