Qwen3-Next 80B-A3B Instruct vs Claude Haiku 4.5 vs GLM-4.5V
Too close to call on our weighted score (GLM-4.5V 49, Claude Haiku 4.5 48, Qwen3-Next 80B-A3B Instruct 39). The right pick depends on what you value most.
Alibaba (Qwen)Qwen3-Next 80B-A3B Instruct
39/100- ECI—
- Price$0.50 / $2.00
- Context131K
AnthropicClaude Haiku 4.5
48/100- ECI142.4
- Price$1.00 / $5.00
- Context200K
Z.ai (Zhipu)GLM-4.5V
49/100- ECI—
- Price$0.60 / $1.80
- Context64K
Too close to call
It is close. Our weighted score puts them within 1 points (GLM-4.5V 49/100, Claude Haiku 4.5 48/100, Qwen3-Next 80B-A3B Instruct 39/100), so choose by what matters most for your work: Qwen3-Next 80B-A3B Instruct on price and Claude Haiku 4.5 for long inputs. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceQwen3-Next 80B-A3B InstructQwen3-Next 80B-A3B Instruct $0.875 · GLM-4.5V $0.90 · Claude Haiku 4.5 $2.00 per 1M tokens (3:1 blend)
- Longest contextClaude Haiku 4.5Claude Haiku 4.5 200,000 · Qwen3-Next 80B-A3B Instruct 131,072 · GLM-4.5V 64,000 tokens
- Widest inputsClaude Haiku 4.5 and GLM-4.5VQwen3-Next 80B-A3B Instruct: Text · Claude Haiku 4.5: Text, Images, PDFs · GLM-4.5V: Text, Images, Video
- Self-hostingQwen3-Next 80B-A3B Instruct and GLM-4.5VPublishes downloadable weights
| Measure | Weight | Qwen3-Next 80B-A3B Instruct | Claude Haiku 4.5 | GLM-4.5V |
|---|---|---|---|---|
| Price | 50% | 53 | 36 | 52 |
| Inputs & features | 30% | 25 | 80 | 70 |
| Context window | 20% | 24 | 32 | 12 |
| Overall | 100% | 39/100 | 48/100 | 49/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Qwen3-Next 80B-A3B InstructAlibaba (Qwen) | Claude Haiku 4.5Anthropic | GLM-4.5VZ.ai (Zhipu) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | 142.4 | — |
| ECI rank | — | #90 of 148 | — |
| GPQA DiamondGraduate-level science questions | — | 71.2% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 66.7% | — |
| SimpleQA VerifiedShort factual questions | — | 13.2% | — |
| Price per million tokens | |||
| Input | $0.50 (best) | $1.00 | $0.60 |
| Output | $2.00 | $5.00 | $1.80 (best) |
| Cached input | — | $0.10 | — |
| Blended (3:1) | $0.875 (best) | $2.00 | $0.90 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Alibaba API | Official Anthropic API | Official Z.AI API |
| Limits | |||
| Context window | 131,072 tokens | 200,000 tokens (best) | 64,000 tokens |
| Max output | 32,768 tokens | 64,000 tokens (best) | 16,384 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | Yes | No |
| Audio | No | No | No |
| Video | No | No | Yes |
| Reasoning | No | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Open | Proprietary | Open |
| API model ID | qwen3-next-80b-a3b-instruct | claude-haiku-4-5 | glm-4.5v |
| API providers | 13 | 34 (best) | 11 |
| Released | Sep 2025 | Oct 15, 2025 | Aug 11, 2025 |
| Knowledge cutoff | Apr 2025 | Feb 28, 2025 | Apr 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Qwen3-Next 80B-A3B Instruct$9.00
- Claude Haiku 4.5$20.00
- GLM-4.5V$9.60
Which should you choose?
Which is better: Qwen3-Next 80B-A3B Instruct, Claude Haiku 4.5 or GLM-4.5V?
It is close. Our weighted score puts them within 1 points (GLM-4.5V 49/100, Claude Haiku 4.5 48/100, Qwen3-Next 80B-A3B Instruct 39/100), so choose by what matters most for your work: Qwen3-Next 80B-A3B Instruct on price and Claude Haiku 4.5 for long inputs. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Qwen3-Next 80B-A3B Instruct, Claude Haiku 4.5 or GLM-4.5V?
Qwen3-Next 80B-A3B Instruct is cheaper at $0.50 input / $2.00 output per million tokens (official Alibaba API price). GLM-4.5V costs $0.60 input / $1.80 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). At a typical mix of three input tokens to one output token, that is $0.875 per million tokens for Qwen3-Next 80B-A3B Instruct versus $0.90 for GLM-4.5V (1× as much) and $2.00 for Claude Haiku 4.5 (2.3× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Qwen3-Next 80B-A3B Instruct has not been scored yet, Claude Haiku 4.5 has an ECI of 142.4 and GLM-4.5V has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3-Next 80B-A3B Instruct, Claude Haiku 4.5 and GLM-4.5V yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
Claude Haiku 4.5 has the largest context window at 200,000 tokens, against 131,072 for Qwen3-Next 80B-A3B Instruct and 64,000 for GLM-4.5V. Maximum output per response: Qwen3-Next 80B-A3B Instruct up to 32,768, Claude Haiku 4.5 up to 64,000, GLM-4.5V up to 16,384 tokens.
Which can read images, PDFs, audio or video?
Qwen3-Next 80B-A3B Instruct accepts text; Claude Haiku 4.5 accepts text, images and PDFs; GLM-4.5V accepts text, images and video. Claude Haiku 4.5 handles the widest range of inputs.
Are any of these open source?
Qwen3-Next 80B-A3B Instruct and GLM-4.5V publishes its weights and can be self-hosted; Claude Haiku 4.5 is proprietary.
Which is newer?
Claude Haiku 4.5 is the newest, released Oct 15, 2025. Qwen3-Next 80B-A3B Instruct came out Sep 2025; GLM-4.5V came out Aug 11, 2025. Knowledge cutoff: Qwen3-Next 80B-A3B Instruct Apr 2025, Claude Haiku 4.5 Feb 28, 2025, GLM-4.5V 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.
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