ZMIME
Comparison · 3 models · Updated Oct 4, 2026

Claude Haiku 4.5 vs Qwen3 Max vs GLM-4.7

Too close to call on our weighted score (Claude Haiku 4.5 58, GLM-4.7 56, Qwen3 Max 50). The right pick depends on what you value most.

  1. Anthropic

    Claude Haiku 4.5

    Released Oct 15, 2025

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

    Qwen3 Max

    Released Sep 23, 2025

    50/100
    • ECI142.4
    • Price$1.20 / $6.00
    • Context262K
  3. Z.ai (Zhipu)

    GLM-4.7

    Released Dec 22, 2025

    56/100
    • ECI143.5
    • Price$0.60 / $2.20
    • Context205K
01 — Verdict

Too close to call

It is close. Our weighted score puts them within 2 points (Claude Haiku 4.5 58/100, GLM-4.7 56/100, Qwen3 Max 50/100), so choose by what matters most for your work: GLM-4.7 for raw capability and Qwen3 Max for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityGLM-4.7Capabilities Index (ECI): GLM-4.7 143.5 · Claude Haiku 4.5 142.4 · Qwen3 Max 142.4
  • Lowest priceGLM-4.7GLM-4.7 $1.00 · Claude Haiku 4.5 $2.00 · Qwen3 Max $2.40 per 1M tokens (3:1 blend)
  • Longest contextQwen3 MaxQwen3 Max 262,144 · GLM-4.7 204,800 · Claude Haiku 4.5 200,000 tokens
  • Widest inputsClaude Haiku 4.5Claude Haiku 4.5: Text, Images, PDFs · Qwen3 Max: Text · GLM-4.7: Text
  • Self-hostingGLM-4.7Publishes downloadable weights
How the score is built
MeasureWeightClaude Haiku 4.5Qwen3 MaxGLM-4.7
CapabilityCapabilities Index (ECI)50%696870
Price25%363250
Inputs & features15%802535
Context window10%323732
Overall100%58/10050/10056/100
02 — Side by side

Every spec in one table

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

Claude Haiku 4.5 vs Qwen3 Max vs GLM-4.7 specifications side by side
SpecificationClaude Haiku 4.5AnthropicQwen3 MaxAlibaba (Qwen)GLM-4.7Z.ai (Zhipu)
Capability
Capabilities Index (ECI)142.4142.4143.5 (best)
ECI rank#90 of 148#91 of 148#84 of 148 (best)
GPQA DiamondGraduate-level science questions71.2%72.6%83.3% (best)
FrontierMath Tiers 1–3Research-level mathematics—19.0%—
OTIS Mock AIME 2024–2025Competition mathematics66.7%73.3%83.3% (best)
SimpleQA VerifiedShort factual questions13.2%48.8% (best)32.2%
Price per million tokens
Input$1.00$1.20$0.60 (best)
Output$5.00$6.00$2.20 (best)
Cached input$0.10 (best)—$0.11
Blended (3:1)$2.00$2.40$1.00 (best)
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Anthropic APIOfficial Alibaba APIOfficial Z.AI API
Limits
Context window200,000 tokens262,144 tokens (best)204,800 tokens
Max output64,000 tokens65,536 tokens131,072 tokens (best)
Inputs and features
TextYesYesYes
ImagesYesNoNo
PDFsYesNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningYesNoYes
Tool callingYesYesYes
Structured outputYesNoNo
Availability
WeightsProprietaryProprietaryOpen
API model IDclaude-haiku-4-5qwen3-maxglm-4.7
API providers34 (best)1620
ReleasedOct 15, 2025Sep 23, 2025Dec 22, 2025
Knowledge cutoffFeb 28, 2025Apr 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.

  • Claude Haiku 4.5$20.00
  • Qwen3 Max$24.00
  • GLM-4.7$10.40
04 — Questions

Which should you choose?

Which is better: Claude Haiku 4.5, Qwen3 Max or GLM-4.7?

It is close. Our weighted score puts them within 2 points (Claude Haiku 4.5 58/100, GLM-4.7 56/100, Qwen3 Max 50/100), so choose by what matters most for your work: GLM-4.7 for raw capability and Qwen3 Max for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Claude Haiku 4.5, Qwen3 Max or GLM-4.7?

GLM-4.7 is cheaper at $0.60 input / $2.20 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 $1.00 per million tokens for GLM-4.7 versus $2.00 for Claude Haiku 4.5 (2× as much) and $2.40 for Qwen3 Max (2.4× as much).

Which scores higher on benchmarks?

GLM-4.7 scores higher on the Capabilities Index (ECI): GLM-4.7 143.5 (#84 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 (141.3–145.6 vs 139.5–144.3), so treat the gap as small. On individual benchmarks: GPQA Diamond — GLM-4.7 83.3%, Qwen3 Max 72.6%, Claude Haiku 4.5 71.2%; OTIS Mock AIME 2024–2025 — GLM-4.7 83.3%, Qwen3 Max 73.3%, Claude Haiku 4.5 66.7%; SimpleQA Verified — Qwen3 Max 48.8%, GLM-4.7 32.2%, Claude Haiku 4.5 13.2%.

Which is better for coding?

There are no published SWE-bench Verified results for Claude Haiku 4.5, Qwen3 Max and GLM-4.7 yet, so there is no like-for-like coding score. On overall capability, GLM-4.7 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-4.7 and 200,000 for Claude Haiku 4.5. Maximum output per response: Claude Haiku 4.5 up to 64,000, Qwen3 Max up to 65,536, GLM-4.7 up to 131,072 tokens.

Which can read images, PDFs, audio or video?

Claude Haiku 4.5 accepts text, images and PDFs; Qwen3 Max accepts text; GLM-4.7 accepts text. Claude Haiku 4.5 handles the widest range of inputs.

Are any of these open source?

GLM-4.7 publishes its weights and can be self-hosted; Claude Haiku 4.5 and Qwen3 Max is proprietary.

Which is newer?

GLM-4.7 is the newest, released Dec 22, 2025. 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, GLM-4.7 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.