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Claude Opus 5.5 vs DeepSeek V4.1 Flash

Claude Opus 5.5 grades higher overall (99.5 against 83.5). DeepSeek V4.1 Flash costs 96% less for the same work.

Claude Opus 5.5

by Anthropic · #1 of 67 overall

Coming soon · price at launch
Context
1M
Input / 1M
$4.00
Output / 1M
$20.00

DeepSeek V4.1 Flash

by DeepSeek · #11 of 67 overall

Coming soon · price at launch
Context
1M
Input / 1M
$0.20
Output / 1M
$0.60

Better overall

Claude Opus 5.5

Grade 99.5 vs 83.5

Cheaper

DeepSeek V4.1 Flash

96% less, $0.30 vs $8.00 blended

Larger context

DeepSeek V4.1 Flash

1M vs 1M tokens

Terminal-Bench 4.0

Claude Opus 5.5

66.4% vs 31.2%

Head to head

Public benchmarks. Longer is better; each value links to its source.

LMArena TextElo-style rating · LMArena (CC BY 4.0) · Oct 15, 2026
Claude Opus 5.5Claude Opus 5.5: 1,508
DeepSeek V4.1 FlashDeepSeek V4.1 Flash: 1,475
LMArena WebDevElo-style rating · LMArena (CC BY 4.0) · Oct 13, 2026
Claude Opus 5.5Claude Opus 5.5: 1,811
DeepSeek V4.1 FlashDeepSeek V4.1 Flash: 1,619
LMArena CodingElo-style rating · LMArena (CC BY 4.0) · Oct 15, 2026
Claude Opus 5.5Claude Opus 5.5: 1,545
DeepSeek V4.1 FlashDeepSeek V4.1 Flash: 1,523
SWE-Bench Pro% of tasks resolved · Scale AI SWE-Bench Pro · Sep 22, 2026 · reference
Claude Opus 5.5Claude Opus 5.5: 89.9%v
DeepSeek V4.1 FlashDeepSeek V4.1 Flash: —
Terminal-Bench 4.0% of tasks passed · Terminal-Bench · Sep 22, 2026 · reference
Claude Opus 5.5Claude Opus 5.5: 66.4%v
DeepSeek V4.1 FlashDeepSeek V4.1 Flash: 31.2%v
Terminal-Bench 3.0% of tasks passed · Terminal-Bench · Sep 10, 2026 · reference
Claude Opus 5.5Claude Opus 5.5: —
DeepSeek V4.1 FlashDeepSeek V4.1 Flash: 30%v
Terminal-Bench 2.1% of tasks passed · Terminal-Bench · Sep 10, 2026 · reference
Claude Opus 5.5Claude Opus 5.5: —
DeepSeek V4.1 FlashDeepSeek V4.1 Flash: 90.6%v

Claude Opus 5.5DeepSeek V4.1 Flashv = reported by the model’s maker. — = no public score yet. Arena bars span the range across every model we grade.

Speed through FullsendAI

Measured through FullsendAI, from one location, Oct 15, 2026, n=20 (5 for long runs).

Claude Opus 5.5DeepSeek V4.1 Flash

Time to first tokenmedian, tick at p90 · lower is faster

Claude Opus 5.5Claude Opus 5.5: —
DeepSeek V4.1 FlashDeepSeek V4.1 Flash: 393 msp90 739

Output speed1,500-token replies, tick at p90

Claude Opus 5.5Claude Opus 5.5: —
DeepSeek V4.1 FlashDeepSeek V4.1 Flash: 162 t/sp90 197

First-try success — for Claude Opus 5.5 and 55/55 for DeepSeek V4.1 Flash. FullsendAI retries busy responses automatically, so a missed first try costs a moment, not an error.

How we measured

Streamed chat completions with default settings, the two models alternating run by run. Time to first token runs from sending the request to the first streamed token, connection included, over short prompts. Output speed is output tokens a second after the first token, on long replies. One location and one afternoon, so treat small differences as noise.

What it costs you

Drag to match your monthly usage.

Claude Opus 5.5$1,600 /month
DeepSeek V4.1 Flash$64.00 /month

DeepSeek V4.1 Flash saves you $1,536 a month at this usage, $18,432 a year.

Capabilities

CapabilityClaude Opus 5.5DeepSeek V4.1 Flash
Reasoning levels through FullsendAI Yes Yes
Reads images through FullsendAI Yes Yes
Open weights— Yes
Tool calling— Yes
JSON output— Yes
Tool calls that worked (measured)—10/10
Valid JSON replies (measured)—10/10

Our coding quick check (ten small Python functions against hidden tests; not a benchmark): — for Claude Opus 5.5, 10/10 for DeepSeek V4.1 Flash.

Maker-published benchmarks

As each maker reports them, with their own harnesses and settings: not graded, and not strictly comparable across makers.

BenchmarkClaude Opus 5.5DeepSeek V4.1 Flash
Terminal-Bench 2.1—90.6%
Terminal-Bench 3.0—30%
Terminal-Bench 4.0—31.2%
DeepSWE v1.1—74.2%
NL2Repo-Bench—64
ProgramBench—20.3%
Codeforces—3,471 rating
SEC-Bench Pro—62.8%
CyberGym—88.1%
ExploitGym—15.3%
HumanEval (base model)—79.4%
BigCodeBench (base model)—60.6%
AutomationBench—54.8%
Agent's Last Exam—31.8%

Each score links to where its maker published it.

At a glance

AttributeClaude Opus 5.5DeepSeek V4.1 Flash
Made byAnthropicDeepSeek
AvailabilityComing soonComing soon
Overall gradeExcellent · 99.5Excellent · 83.5
Overall rank#1 of 67#11 of 67
Input price$4.00 per 1M$0.20 per 1M
Output price$20.00 per 1M$0.60 per 1M
Context window1,000,000 tokens1,048,576 tokens
Reasoning levelsYesYes
Reads imagesYesYes
Model IDclaude-opus-5-5deepseek-v4.1-flash
Model card: what the makers publish
FactClaude Opus 5.5DeepSeek V4.1 Flash
Released—Sep 10, 2026
Made by—DeepSeek (DeepSeek-AI)
Licence—MIT License (repository and model weights)
Commercial use—Allowed (MIT License permits use, modification, distribution, sublicensing and sale)
Open weights—Yes
Parameters—552B backbone parameters (includes 196B Engram conditional-memory parameters per the card's architecture notes)
Active parameters—8B per token during prefill / 16B per token during decode
Mixture of experts—Yes: 1 shared + 384 routed experts per MoE layer, 6 routed experts active per token
Architecture—Causal Encoder-Decoder (CED): 40-layer Transformer = 20-layer causal encoder + 20-layer decoder; decoder global KV projected from final encoder states. Compressed Sparse Attention 2 (CSA2, Full/Reindex/Reuse layer modes, Hierarchical Sparse Indexer), FP4 main KV cache (E2M1, one E4M3 scale per 16 channels), ~890 bytes/token global KV cache (~1/4 of DeepSeek-V4-Flash), SWA Bounded Replay, Single-Pass mHC, Engram conditional memory (196B params), DSpark speculative decoding, DeepSeek-ViT vision encoder + 2-layer MLP projector.
Context window—1,048,576 tokens
Max output—384K (DeepSeek's own API, 'MAXIMUM: 384K')
Input—Text, Image
Output—Text
Reasoning—Thinking mode with continuously controllable reasoning effort (integer 1-100). DeepSeek API: thinking on by default (effort 'high'); toggle via {"thinking": {"type": "enabled"|"disabled"}}, effort via reasoning_effort low/high/max. In thinking mode temperature/penalties are ignored; reasoning returned in reasoning_content.
Tool calling—Yes
JSON output—JSON Output via response_format {'type':'json_object'} (prompt must mention 'json')
Recommended sampling—temperature 1.0, top_p 0.95 or 1.0, context_window 1M, max_tokens >= 256K
Training data—Pre-trained from scratch on a 45T-token multimodal corpus; context extended to 1M at 34T tokens
Other features—Chat Prefix Completion (Beta), FIM Completion (Beta, non-thinking mode only), Responses API and Anthropic-format API on DeepSeek's own endpoint; context caching (cache-hit pricing); vision
Sources

Try both with one key

Same endpoint, same key, both hosted in the USA. Change one word to switch models, in Claude Code, Cursor, Cline or your own code.

Get your API key
# Ask either model the same thing
curl https://fullsendai.com/v1/chat/completions \
  -H "Authorization: Bearer $FULLSEND_API_KEY" \
  -d '{"model": "claude-opus-5-5", "messages": [...]}'

# …then swap one word
  -d '{"model": "deepseek-v4.1-flash", "messages": [...]}'

Questions

Is Claude Opus 5.5 or DeepSeek V4.1 Flash better?

Claude Opus 5.5 grades 99.5 against 83.5 for DeepSeek V4.1 Flash, from public benchmarks.

Which is cheaper, Claude Opus 5.5 or DeepSeek V4.1 Flash?

DeepSeek V4.1 Flash: $0.20 in and $0.60 out per million tokens, against $4.00 and $20.00 through FullsendAI.

Which has the larger context window?

DeepSeek V4.1 Flash, with 1,048,576 tokens.

Can I use both with one API key?

Yes, once they launch: both are coming soon, at the prices shown, and both will use the same FullsendAI key.

Compare with others

Model rankingsAll benchmarksCompare other models

Scores: LMArena (CC BY 4.0), Scale AI SWE-Bench Pro, Terminal-Bench, and model makers’ published results where marked v. Prices are FullsendAI’s, per million tokens. Data as of Oct 28, 2026.