Models, measured side by side
Claude Opus 5.5 vs Qwen3.8 2.4T A95B
Compare Claude Opus 5.5, Qwen3.8 2.4T A95B by token pricing, context length, benchmark results, speed and tool support.
Monthly workload
Monthly cost breakdown
InputOutput
Claude Opus 5.5
$180 / mo
Qwen3.8 2.4T A95B
$70 / mo
Performance comparison
Claude Opus 5.5
57.6
Qwen3.8 2.4T A95B
39.9
Overview
Pricing & capacity
| Pricing & capacity | Claude Opus 5.5 | Qwen3.8 2.4T A95B |
|---|---|---|
| Input / 1M tokens | $4.00 | $2.00 |
| Output / 1M tokens | $20 | $6.00 |
| Cached input / 1M | $0.20 | $0.25 |
| Monthly cost | $180 | $70 |
| Context window | 1M | 1M |
| Maximum output | 128K | 131K |
Input / 1M tokens
- Claude Opus 5.5
- $4.00
- Qwen3.8 2.4T A95B
- $2.00
Output / 1M tokens
- Claude Opus 5.5
- $20
- Qwen3.8 2.4T A95B
- $6.00
Cached input / 1M
- Claude Opus 5.5
- $0.20
- Qwen3.8 2.4T A95B
- $0.25
Monthly cost
- Claude Opus 5.5
- $180
- Qwen3.8 2.4T A95B
- $70
Context window
- Claude Opus 5.5
- 1M
- Qwen3.8 2.4T A95B
- 1M
Maximum output
- Claude Opus 5.5
- 128K
- Qwen3.8 2.4T A95B
- 131K
Benchmarks & performance
| Benchmarks & performance | Claude Opus 5.5 | Qwen3.8 2.4T A95B |
|---|---|---|
| Intelligence Index | 57.6 | 39.9 |
| GPQA | Not listed | 93.5% |
| Humanity’s Last Exam | 61.4% | 42.4% |
| SciCode | 66.9% | 54.1% |
| Output speed | 91 tokens/s | 38 tokens/s |
| Time to first token | 755.54 s | 2.75 s |
| DesignArena rating | 1,407 | Not listed |
| DesignArena win rate | 65.3% | Not listed |
Intelligence Index
- Claude Opus 5.5
- 57.6
- Qwen3.8 2.4T A95B
- 39.9
GPQA
- Claude Opus 5.5
- Not listed
- Qwen3.8 2.4T A95B
- 93.5%
Humanity’s Last Exam
- Claude Opus 5.5
- 61.4%
- Qwen3.8 2.4T A95B
- 42.4%
SciCode
- Claude Opus 5.5
- 66.9%
- Qwen3.8 2.4T A95B
- 54.1%
Output speed
- Claude Opus 5.5
- 91 tokens/s
- Qwen3.8 2.4T A95B
- 38 tokens/s
Time to first token
- Claude Opus 5.5
- 755.54 s
- Qwen3.8 2.4T A95B
- 2.75 s
DesignArena rating
- Claude Opus 5.5
- 1,407
- Qwen3.8 2.4T A95B
- Not listed
DesignArena win rate
- Claude Opus 5.5
- 65.3%
- Qwen3.8 2.4T A95B
- Not listed
Tools & features
| Tools & features | Claude Opus 5.5 | Qwen3.8 2.4T A95B |
|---|---|---|
| Function calling | Supported | Supported |
| Structured outputs | Supported | Supported |
| JSON mode | Supported | Supported |
| Reasoning | Supported | Supported |
| Log probabilities | Not listed | Supported |
| Deterministic seed | Not listed | Supported |
| Prompt caching | Supported | Supported |
Function calling
- Claude Opus 5.5
- Supported
- Qwen3.8 2.4T A95B
- Supported
Structured outputs
- Claude Opus 5.5
- Supported
- Qwen3.8 2.4T A95B
- Supported
JSON mode
- Claude Opus 5.5
- Supported
- Qwen3.8 2.4T A95B
- Supported
Reasoning
- Claude Opus 5.5
- Supported
- Qwen3.8 2.4T A95B
- Supported
Log probabilities
- Claude Opus 5.5
- Not listed
- Qwen3.8 2.4T A95B
- Supported
Deterministic seed
- Claude Opus 5.5
- Not listed
- Qwen3.8 2.4T A95B
- Supported
Prompt caching
- Claude Opus 5.5
- Supported
- Qwen3.8 2.4T A95B
- Supported
API & availability
| API & availability | Claude Opus 5.5 | Qwen3.8 2.4T A95B |
|---|---|---|
| API identifier | claude-opus-5.5 | qwen3.8-2.4t-a95b |
| Prices checked | Oct 8, 2026 | Oct 8, 2026 |
API identifier
- Claude Opus 5.5
claude-opus-5.5- Qwen3.8 2.4T A95B
qwen3.8-2.4t-a95b
Prices checked
- Claude Opus 5.5
- Oct 8, 2026
- Qwen3.8 2.4T A95B
- Oct 8, 2026
About the models
Claude Opus 5.5
Claude Opus 5.5 is Anthropic's flagship model for demanding reasoning, coding, and long-horizon agentic work, succeeding Claude Opus 5. It is particularly strong at multi-step changes in large codebases, code...
Full pricing & detailsQwen3.8 2.4T A95B
Qwen3.8 2.4T A95B is an open-weight sparse mixture-of-experts model from Qwen and the open-weight variant of [Qwen3.8 Max](/qwen/qwen3.8-max), with 95 billion active parameters out of 2.4 trillion total. It is...
Full pricing & detailsComparison FAQ
Claude Opus 5.5: $4.00 input and $20 output per million tokens. Qwen3.8 2.4T A95B: $2.00 input and $6.00 output per million tokens. The cheaper choice depends on your input-to-output ratio; a model can have a lower input rate but a higher output rate.
